Add Tavily Research and get Research (#5483)

* Add Tavily Research and get Research

- Added tavily research with docs to crew AI

- Added tavily get research with docs to crew AI

* Update `tavily-python` installation instructions and adjust version constraints

- Changed installation command from `pip install` to `uv add` for `tavily-python` in multiple documentation files.
- Updated version constraint for `tavily-python` in `pyproject.toml` from `>=0.7.14` to `~=0.7.14`.
- Modified the `exclude-newer` date in `uv.lock` to `2026-04-23T07:00:00Z`.

* Add Tavily Research Tool documentation in multiple languages

- Introduced `TavilyResearchTool` documentation in English, Arabic, Korean, and Portuguese.
- Updated `docs.json` to include paths for the new documentation files.
- The `TavilyResearchTool` allows CrewAI agents to perform multi-step research tasks and generate cited reports using the Tavily Research API.

* Fix Tavily research CI failures

---------

Co-authored-by: lorenzejay <lorenzejaytech@gmail.com>
Co-authored-by: Evan Rimer <evan.rimer@tavily.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>

docs/ar/tools/search-research/tavilyextractortool.mdx

@@ -12,7 +12,7 @@ mode: "wide"
 لاستخدام `TavilyExtractorTool`، تحتاج إلى تثبيت مكتبة `tavily-python`:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 تحتاج أيضاً إلى تعيين مفتاح Tavily API كمتغير بيئة:

docs/ar/tools/search-research/tavilyresearchtool.mdx

@@ -0,0 +1,125 @@
+---
+title: "Tavily Research Tool"
+description: "Run multi-step research tasks and get cited reports using the Tavily Research API"
+icon: "flask"
+mode: "wide"
+---
+
+The `TavilyResearchTool` lets CrewAI agents kick off Tavily research tasks, returning a synthesized, cited report (or a stream of progress events) instead of raw search results. Use it when an agent needs an investigative answer rather than a single web search.
+
+## Installation
+
+To use the `TavilyResearchTool`, install the `tavily-python` library alongside `crewai-tools`:
+
+```shell
+uv add 'crewai[tools]' tavily-python
+```
+
+## Environment Variables
+
+Set your Tavily API key:
+
+```bash
+export TAVILY_API_KEY='your_tavily_api_key'
+```
+
+Get an API key at [https://app.tavily.com/](https://app.tavily.com/) (sign up, then create a key).
+
+## Example Usage
+
+```python
+import os
+from crewai import Agent, Crew, Task
+from crewai_tools import TavilyResearchTool
+
+# Ensure TAVILY_API_KEY is set in your environment
+# os.environ["TAVILY_API_KEY"] = "YOUR_API_KEY"
+
+tavily_tool = TavilyResearchTool()
+
+researcher = Agent(
+    role="Research Analyst",
+    goal="Investigate questions and produce concise, well-cited briefings.",
+    backstory=(
+        "You are a meticulous analyst who delegates web research to the Tavily "
+        "Research tool, then synthesizes the findings into short briefings."
+    ),
+    tools=[tavily_tool],
+    verbose=True,
+)
+
+research_task = Task(
+    description=(
+        "Investigate notable open-source agent orchestration frameworks released "
+        "in the last six months and summarize their differentiators."
+    ),
+    expected_output="A bulleted briefing with citations.",
+    agent=researcher,
+)
+
+crew = Crew(agents=[researcher], tasks=[research_task])
+print(crew.kickoff())
+```
+
+## Configuration Options
+
+The `TavilyResearchTool` accepts the following arguments — all can be set on the tool instance (defaults for every call) or per-call via the agent's tool input:
+
+- `input` (str): **Required.** The research task or question to investigate.
+- `model` (Literal["mini", "pro", "auto"]): The Tavily research model. `"auto"` lets Tavily pick; `"mini"` is faster/cheaper; `"pro"` is the most capable. Defaults to `"auto"`.
+- `output_schema` (dict | None): Optional JSON Schema that structures the research output. Useful when you want strictly typed results.
+- `stream` (bool): When `True`, the tool returns an iterator of SSE chunks emitting research progress and the final result instead of a single string. Defaults to `False`.
+- `citation_format` (Literal["numbered", "mla", "apa", "chicago"]): Citation format for the report. Defaults to `"numbered"`.
+
+## Advanced Usage
+
+### Configure defaults on the tool instance
+
+```python
+from crewai_tools import TavilyResearchTool
+
+tavily_tool = TavilyResearchTool(
+    model="pro",                # use Tavily's most capable research model
+    citation_format="apa",      # APA-style citations
+)
+```
+
+### Stream research progress
+
+When `stream=True`, the tool returns a generator (or async generator from `_arun`) of SSE chunks so your application can surface incremental progress:
+
+```python
+tavily_tool = TavilyResearchTool(stream=True)
+
+for chunk in tavily_tool.run(input="Summarize recent advances in retrieval-augmented generation."):
+    print(chunk)
+```
+
+### Structured output via JSON Schema
+
+Pass an `output_schema` when you need a typed result instead of a free-form report:
+
+```python
+output_schema = {
+    "type": "object",
+    "properties": {
+        "summary": {"type": "string"},
+        "key_points": {"type": "array", "items": {"type": "string"}},
+        "sources": {"type": "array", "items": {"type": "string"}},
+    },
+    "required": ["summary", "key_points", "sources"],
+}
+
+tavily_tool = TavilyResearchTool(output_schema=output_schema)
+```
+
+## Features
+
+- **End-to-end research**: Returns a synthesized, cited report rather than raw search hits.
+- **Model selection**: Trade off cost, speed, and depth via `mini`, `pro`, or `auto`.
+- **Streaming**: Stream incremental progress and results as SSE chunks for responsive UIs.
+- **Structured output**: Coerce results to a JSON Schema you define.
+- **Multiple citation styles**: Choose from numbered, MLA, APA, or Chicago citations.
+- **Sync and async**: Use either `_run` or `_arun` depending on your application's runtime.
+
+Refer to the [Tavily API documentation](https://docs.tavily.com/) for full details on the Research API.

docs/ar/tools/search-research/tavilysearchtool.mdx

@@ -12,7 +12,7 @@ mode: "wide"
 لاستخدام `TavilySearchTool`، تحتاج إلى تثبيت مكتبة `tavily-python`:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 ## متغيرات البيئة

docs/docs.json

@@ -247,6 +247,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -1199,6 +1200,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -1675,6 +1677,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -2151,6 +2154,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -2627,6 +2631,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -3102,6 +3107,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -3576,6 +3582,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -4050,6 +4057,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -4524,6 +4532,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -5000,6 +5009,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -5475,6 +5485,7 @@
                           "en/tools/search-research/youtubevideosearchtool",
                           "en/tools/search-research/tavilysearchtool",
                           "en/tools/search-research/tavilyextractortool",
+                          "en/tools/search-research/tavilyresearchtool",
                           "en/tools/search-research/arxivpapertool",
                           "en/tools/search-research/serpapi-googlesearchtool",
                           "en/tools/search-research/serpapi-googleshoppingtool",
@@ -11512,6 +11523,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -12454,6 +12466,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -12925,6 +12938,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -13396,6 +13410,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -13867,6 +13882,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -14337,6 +14353,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -14807,6 +14824,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -15277,6 +15295,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -15746,6 +15765,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -16215,6 +16235,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -16685,6 +16706,7 @@
                           "ko/tools/search-research/youtubevideosearchtool",
                           "ko/tools/search-research/tavilysearchtool",
                           "ko/tools/search-research/tavilyextractortool",
+                          "ko/tools/search-research/tavilyresearchtool",
                           "ko/tools/search-research/arxivpapertool",
                           "ko/tools/search-research/serpapi-googlesearchtool",
                           "ko/tools/search-research/serpapi-googleshoppingtool",
@@ -17186,6 +17208,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -18128,6 +18151,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -18599,6 +18623,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -19070,6 +19095,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -19541,6 +19567,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -20011,6 +20038,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -20481,6 +20509,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -20951,6 +20980,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -21420,6 +21450,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -21889,6 +21920,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",
@@ -22359,6 +22391,7 @@
                           "ar/tools/search-research/youtubevideosearchtool",
                           "ar/tools/search-research/tavilysearchtool",
                           "ar/tools/search-research/tavilyextractortool",
+                          "ar/tools/search-research/tavilyresearchtool",
                           "ar/tools/search-research/arxivpapertool",
                           "ar/tools/search-research/serpapi-googlesearchtool",
                           "ar/tools/search-research/serpapi-googleshoppingtool",

docs/en/tools/search-research/tavilyextractortool.mdx

@@ -12,7 +12,7 @@ The `TavilyExtractorTool` allows CrewAI agents to extract structured content fro
 To use the `TavilyExtractorTool`, you need to install the `tavily-python` library:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 You also need to set your Tavily API key as an environment variable:

docs/en/tools/search-research/tavilyresearchtool.mdx

@@ -0,0 +1,125 @@
+---
+title: "Tavily Research Tool"
+description: "Run multi-step research tasks and get cited reports using the Tavily Research API"
+icon: "flask"
+mode: "wide"
+---
+
+The `TavilyResearchTool` lets CrewAI agents kick off Tavily research tasks, returning a synthesized, cited report (or a stream of progress events) instead of raw search results. Use it when an agent needs an investigative answer rather than a single web search.
+
+## Installation
+
+To use the `TavilyResearchTool`, install the `tavily-python` library alongside `crewai-tools`:
+
+```shell
+uv add 'crewai[tools]' tavily-python
+```
+
+## Environment Variables
+
+Set your Tavily API key:
+
+```bash
+export TAVILY_API_KEY='your_tavily_api_key'
+```
+
+Get an API key at [https://app.tavily.com/](https://app.tavily.com/) (sign up, then create a key).
+
+## Example Usage
+
+```python
+import os
+from crewai import Agent, Crew, Task
+from crewai_tools import TavilyResearchTool
+
+# Ensure TAVILY_API_KEY is set in your environment
+# os.environ["TAVILY_API_KEY"] = "YOUR_API_KEY"
+
+tavily_tool = TavilyResearchTool()
+
+researcher = Agent(
+    role="Research Analyst",
+    goal="Investigate questions and produce concise, well-cited briefings.",
+    backstory=(
+        "You are a meticulous analyst who delegates web research to the Tavily "
+        "Research tool, then synthesizes the findings into short briefings."
+    ),
+    tools=[tavily_tool],
+    verbose=True,
+)
+
+research_task = Task(
+    description=(
+        "Investigate notable open-source agent orchestration frameworks released "
+        "in the last six months and summarize their differentiators."
+    ),
+    expected_output="A bulleted briefing with citations.",
+    agent=researcher,
+)
+
+crew = Crew(agents=[researcher], tasks=[research_task])
+print(crew.kickoff())
+```
+
+## Configuration Options
+
+The `TavilyResearchTool` accepts the following arguments — all can be set on the tool instance (defaults for every call) or per-call via the agent's tool input:
+
+- `input` (str): **Required.** The research task or question to investigate.
+- `model` (Literal["mini", "pro", "auto"]): The Tavily research model. `"auto"` lets Tavily pick; `"mini"` is faster/cheaper; `"pro"` is the most capable. Defaults to `"auto"`.
+- `output_schema` (dict | None): Optional JSON Schema that structures the research output. Useful when you want strictly typed results.
+- `stream` (bool): When `True`, the tool returns an iterator of SSE chunks emitting research progress and the final result instead of a single string. Defaults to `False`.
+- `citation_format` (Literal["numbered", "mla", "apa", "chicago"]): Citation format for the report. Defaults to `"numbered"`.
+
+## Advanced Usage
+
+### Configure defaults on the tool instance
+
+```python
+from crewai_tools import TavilyResearchTool
+
+tavily_tool = TavilyResearchTool(
+    model="pro",                # use Tavily's most capable research model
+    citation_format="apa",      # APA-style citations
+)
+```
+
+### Stream research progress
+
+When `stream=True`, the tool returns a generator (or async generator from `_arun`) of SSE chunks so your application can surface incremental progress:
+
+```python
+tavily_tool = TavilyResearchTool(stream=True)
+
+for chunk in tavily_tool.run(input="Summarize recent advances in retrieval-augmented generation."):
+    print(chunk)
+```
+
+### Structured output via JSON Schema
+
+Pass an `output_schema` when you need a typed result instead of a free-form report:
+
+```python
+output_schema = {
+    "type": "object",
+    "properties": {
+        "summary": {"type": "string"},
+        "key_points": {"type": "array", "items": {"type": "string"}},
+        "sources": {"type": "array", "items": {"type": "string"}},
+    },
+    "required": ["summary", "key_points", "sources"],
+}
+
+tavily_tool = TavilyResearchTool(output_schema=output_schema)
+```
+
+## Features
+
+- **End-to-end research**: Returns a synthesized, cited report rather than raw search hits.
+- **Model selection**: Trade off cost, speed, and depth via `mini`, `pro`, or `auto`.
+- **Streaming**: Stream incremental progress and results as SSE chunks for responsive UIs.
+- **Structured output**: Coerce results to a JSON Schema you define.
+- **Multiple citation styles**: Choose from numbered, MLA, APA, or Chicago citations.
+- **Sync and async**: Use either `_run` or `_arun` depending on your application's runtime.
+
+Refer to the [Tavily API documentation](https://docs.tavily.com/) for full details on the Research API.

docs/en/tools/search-research/tavilysearchtool.mdx

@@ -12,7 +12,7 @@ The `TavilySearchTool` provides an interface to the Tavily Search API, enabling
 To use the `TavilySearchTool`, you need to install the `tavily-python` library:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 ## Environment Variables

docs/ko/tools/search-research/tavilyextractortool.mdx

@@ -12,7 +12,7 @@ mode: "wide"
 `TavilyExtractorTool`을 사용하려면 `tavily-python` 라이브러리를 설치해야 합니다:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 또한 Tavily API 키를 환경 변수로 설정해야 합니다:

docs/ko/tools/search-research/tavilyresearchtool.mdx

@@ -0,0 +1,125 @@
+---
+title: "Tavily Research Tool"
+description: "Run multi-step research tasks and get cited reports using the Tavily Research API"
+icon: "flask"
+mode: "wide"
+---
+
+The `TavilyResearchTool` lets CrewAI agents kick off Tavily research tasks, returning a synthesized, cited report (or a stream of progress events) instead of raw search results. Use it when an agent needs an investigative answer rather than a single web search.
+
+## Installation
+
+To use the `TavilyResearchTool`, install the `tavily-python` library alongside `crewai-tools`:
+
+```shell
+uv add 'crewai[tools]' tavily-python
+```
+
+## Environment Variables
+
+Set your Tavily API key:
+
+```bash
+export TAVILY_API_KEY='your_tavily_api_key'
+```
+
+Get an API key at [https://app.tavily.com/](https://app.tavily.com/) (sign up, then create a key).
+
+## Example Usage
+
+```python
+import os
+from crewai import Agent, Crew, Task
+from crewai_tools import TavilyResearchTool
+
+# Ensure TAVILY_API_KEY is set in your environment
+# os.environ["TAVILY_API_KEY"] = "YOUR_API_KEY"
+
+tavily_tool = TavilyResearchTool()
+
+researcher = Agent(
+    role="Research Analyst",
+    goal="Investigate questions and produce concise, well-cited briefings.",
+    backstory=(
+        "You are a meticulous analyst who delegates web research to the Tavily "
+        "Research tool, then synthesizes the findings into short briefings."
+    ),
+    tools=[tavily_tool],
+    verbose=True,
+)
+
+research_task = Task(
+    description=(
+        "Investigate notable open-source agent orchestration frameworks released "
+        "in the last six months and summarize their differentiators."
+    ),
+    expected_output="A bulleted briefing with citations.",
+    agent=researcher,
+)
+
+crew = Crew(agents=[researcher], tasks=[research_task])
+print(crew.kickoff())
+```
+
+## Configuration Options
+
+The `TavilyResearchTool` accepts the following arguments — all can be set on the tool instance (defaults for every call) or per-call via the agent's tool input:
+
+- `input` (str): **Required.** The research task or question to investigate.
+- `model` (Literal["mini", "pro", "auto"]): The Tavily research model. `"auto"` lets Tavily pick; `"mini"` is faster/cheaper; `"pro"` is the most capable. Defaults to `"auto"`.
+- `output_schema` (dict | None): Optional JSON Schema that structures the research output. Useful when you want strictly typed results.
+- `stream` (bool): When `True`, the tool returns an iterator of SSE chunks emitting research progress and the final result instead of a single string. Defaults to `False`.
+- `citation_format` (Literal["numbered", "mla", "apa", "chicago"]): Citation format for the report. Defaults to `"numbered"`.
+
+## Advanced Usage
+
+### Configure defaults on the tool instance
+
+```python
+from crewai_tools import TavilyResearchTool
+
+tavily_tool = TavilyResearchTool(
+    model="pro",                # use Tavily's most capable research model
+    citation_format="apa",      # APA-style citations
+)
+```
+
+### Stream research progress
+
+When `stream=True`, the tool returns a generator (or async generator from `_arun`) of SSE chunks so your application can surface incremental progress:
+
+```python
+tavily_tool = TavilyResearchTool(stream=True)
+
+for chunk in tavily_tool.run(input="Summarize recent advances in retrieval-augmented generation."):
+    print(chunk)
+```
+
+### Structured output via JSON Schema
+
+Pass an `output_schema` when you need a typed result instead of a free-form report:
+
+```python
+output_schema = {
+    "type": "object",
+    "properties": {
+        "summary": {"type": "string"},
+        "key_points": {"type": "array", "items": {"type": "string"}},
+        "sources": {"type": "array", "items": {"type": "string"}},
+    },
+    "required": ["summary", "key_points", "sources"],
+}
+
+tavily_tool = TavilyResearchTool(output_schema=output_schema)
+```
+
+## Features
+
+- **End-to-end research**: Returns a synthesized, cited report rather than raw search hits.
+- **Model selection**: Trade off cost, speed, and depth via `mini`, `pro`, or `auto`.
+- **Streaming**: Stream incremental progress and results as SSE chunks for responsive UIs.
+- **Structured output**: Coerce results to a JSON Schema you define.
+- **Multiple citation styles**: Choose from numbered, MLA, APA, or Chicago citations.
+- **Sync and async**: Use either `_run` or `_arun` depending on your application's runtime.
+
+Refer to the [Tavily API documentation](https://docs.tavily.com/) for full details on the Research API.

docs/ko/tools/search-research/tavilysearchtool.mdx

@@ -12,7 +12,7 @@ mode: "wide"
 `TavilySearchTool`을 사용하려면 `tavily-python` 라이브러리를 설치해야 합니다:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 ## 환경 변수

docs/pt-BR/tools/search-research/tavilyextractortool.mdx

@@ -12,7 +12,7 @@ The `TavilyExtractorTool` allows CrewAI agents to extract structured content fro
 To use the `TavilyExtractorTool`, you need to install the `tavily-python` library:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 You also need to set your Tavily API key as an environment variable:

docs/pt-BR/tools/search-research/tavilyresearchtool.mdx

@@ -0,0 +1,125 @@
+---
+title: "Tavily Research Tool"
+description: "Run multi-step research tasks and get cited reports using the Tavily Research API"
+icon: "flask"
+mode: "wide"
+---
+
+The `TavilyResearchTool` lets CrewAI agents kick off Tavily research tasks, returning a synthesized, cited report (or a stream of progress events) instead of raw search results. Use it when an agent needs an investigative answer rather than a single web search.
+
+## Installation
+
+To use the `TavilyResearchTool`, install the `tavily-python` library alongside `crewai-tools`:
+
+```shell
+uv add 'crewai[tools]' tavily-python
+```
+
+## Environment Variables
+
+Set your Tavily API key:
+
+```bash
+export TAVILY_API_KEY='your_tavily_api_key'
+```
+
+Get an API key at [https://app.tavily.com/](https://app.tavily.com/) (sign up, then create a key).
+
+## Example Usage
+
+```python
+import os
+from crewai import Agent, Crew, Task
+from crewai_tools import TavilyResearchTool
+
+# Ensure TAVILY_API_KEY is set in your environment
+# os.environ["TAVILY_API_KEY"] = "YOUR_API_KEY"
+
+tavily_tool = TavilyResearchTool()
+
+researcher = Agent(
+    role="Research Analyst",
+    goal="Investigate questions and produce concise, well-cited briefings.",
+    backstory=(
+        "You are a meticulous analyst who delegates web research to the Tavily "
+        "Research tool, then synthesizes the findings into short briefings."
+    ),
+    tools=[tavily_tool],
+    verbose=True,
+)
+
+research_task = Task(
+    description=(
+        "Investigate notable open-source agent orchestration frameworks released "
+        "in the last six months and summarize their differentiators."
+    ),
+    expected_output="A bulleted briefing with citations.",
+    agent=researcher,
+)
+
+crew = Crew(agents=[researcher], tasks=[research_task])
+print(crew.kickoff())
+```
+
+## Configuration Options
+
+The `TavilyResearchTool` accepts the following arguments — all can be set on the tool instance (defaults for every call) or per-call via the agent's tool input:
+
+- `input` (str): **Required.** The research task or question to investigate.
+- `model` (Literal["mini", "pro", "auto"]): The Tavily research model. `"auto"` lets Tavily pick; `"mini"` is faster/cheaper; `"pro"` is the most capable. Defaults to `"auto"`.
+- `output_schema` (dict | None): Optional JSON Schema that structures the research output. Useful when you want strictly typed results.
+- `stream` (bool): When `True`, the tool returns an iterator of SSE chunks emitting research progress and the final result instead of a single string. Defaults to `False`.
+- `citation_format` (Literal["numbered", "mla", "apa", "chicago"]): Citation format for the report. Defaults to `"numbered"`.
+
+## Advanced Usage
+
+### Configure defaults on the tool instance
+
+```python
+from crewai_tools import TavilyResearchTool
+
+tavily_tool = TavilyResearchTool(
+    model="pro",                # use Tavily's most capable research model
+    citation_format="apa",      # APA-style citations
+)
+```
+
+### Stream research progress
+
+When `stream=True`, the tool returns a generator (or async generator from `_arun`) of SSE chunks so your application can surface incremental progress:
+
+```python
+tavily_tool = TavilyResearchTool(stream=True)
+
+for chunk in tavily_tool.run(input="Summarize recent advances in retrieval-augmented generation."):
+    print(chunk)
+```
+
+### Structured output via JSON Schema
+
+Pass an `output_schema` when you need a typed result instead of a free-form report:
+
+```python
+output_schema = {
+    "type": "object",
+    "properties": {
+        "summary": {"type": "string"},
+        "key_points": {"type": "array", "items": {"type": "string"}},
+        "sources": {"type": "array", "items": {"type": "string"}},
+    },
+    "required": ["summary", "key_points", "sources"],
+}
+
+tavily_tool = TavilyResearchTool(output_schema=output_schema)
+```
+
+## Features
+
+- **End-to-end research**: Returns a synthesized, cited report rather than raw search hits.
+- **Model selection**: Trade off cost, speed, and depth via `mini`, `pro`, or `auto`.
+- **Streaming**: Stream incremental progress and results as SSE chunks for responsive UIs.
+- **Structured output**: Coerce results to a JSON Schema you define.
+- **Multiple citation styles**: Choose from numbered, MLA, APA, or Chicago citations.
+- **Sync and async**: Use either `_run` or `_arun` depending on your application's runtime.
+
+Refer to the [Tavily API documentation](https://docs.tavily.com/) for full details on the Research API.

docs/pt-BR/tools/search-research/tavilysearchtool.mdx

@@ -12,7 +12,7 @@ The `TavilySearchTool` provides an interface to the Tavily Search API, enabling
 To use the `TavilySearchTool`, you need to install the `tavily-python` library:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 ## Environment Variables

lib/crewai-tools/pyproject.toml

@@ -69,7 +69,7 @@ linkup-sdk = [
     "linkup-sdk>=0.2.2",
 ]
 tavily-python = [
-    "tavily-python>=0.5.4",
+    "tavily-python~=0.7.14",
 ]
 hyperbrowser = [
     "hyperbrowser>=0.18.0",

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -197,6 +197,12 @@ from crewai_tools.tools.stagehand_tool.stagehand_tool import StagehandTool
 from crewai_tools.tools.tavily_extractor_tool.tavily_extractor_tool import (
     TavilyExtractorTool,
 )
+from crewai_tools.tools.tavily_get_research_tool.tavily_get_research_tool import (
+    TavilyGetResearchTool,
+)
+from crewai_tools.tools.tavily_research_tool.tavily_research_tool import (
+    TavilyResearchTool,
+)
 from crewai_tools.tools.tavily_search_tool.tavily_search_tool import TavilySearchTool
 from crewai_tools.tools.txt_search_tool.txt_search_tool import TXTSearchTool
 from crewai_tools.tools.vision_tool.vision_tool import VisionTool
@@ -310,6 +316,8 @@ __all__ = [
     "StagehandTool",
     "TXTSearchTool",
     "TavilyExtractorTool",
+    "TavilyGetResearchTool",
+    "TavilyResearchTool",
     "TavilySearchTool",
     "VisionTool",
     "WeaviateVectorSearchTool",

lib/crewai-tools/src/crewai_tools/tools/__init__.py

@@ -184,6 +184,12 @@ from crewai_tools.tools.stagehand_tool.stagehand_tool import StagehandTool
 from crewai_tools.tools.tavily_extractor_tool.tavily_extractor_tool import (
     TavilyExtractorTool,
 )
+from crewai_tools.tools.tavily_get_research_tool.tavily_get_research_tool import (
+    TavilyGetResearchTool,
+)
+from crewai_tools.tools.tavily_research_tool.tavily_research_tool import (
+    TavilyResearchTool,
+)
 from crewai_tools.tools.tavily_search_tool.tavily_search_tool import TavilySearchTool
 from crewai_tools.tools.txt_search_tool.txt_search_tool import TXTSearchTool
 from crewai_tools.tools.vision_tool.vision_tool import VisionTool
@@ -293,6 +299,8 @@ __all__ = [
     "StagehandTool",
     "TXTSearchTool",
     "TavilyExtractorTool",
+    "TavilyGetResearchTool",
+    "TavilyResearchTool",
     "TavilySearchTool",
     "VisionTool",
     "WeaviateVectorSearchTool",

lib/crewai-tools/src/crewai_tools/tools/tavily_extractor_tool/README.md

@@ -9,7 +9,7 @@ The `TavilyExtractorTool` allows CrewAI agents to extract structured content fro
 To use the `TavilyExtractorTool`, you need to install the `tavily-python` library:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 You also need to set your Tavily API key as an environment variable:

lib/crewai-tools/src/crewai_tools/tools/tavily_get_research_tool/README.md

@@ -0,0 +1,44 @@
+# Tavily Get Research Tool
+
+## Description
+
+The `TavilyGetResearchTool` provides an interface to Tavily's research status endpoint through the Tavily Python SDK. It retrieves the current status and results of an existing Tavily research task by `request_id`.
+
+## Installation
+
+To use the `TavilyGetResearchTool`, you need to install the `tavily-python` library:
+
+```shell
+uv add 'crewai[tools]' tavily-python
+```
+
+## Environment Variables
+
+Ensure your Tavily API key is set as an environment variable:
+
+```bash
+export TAVILY_API_KEY='your_tavily_api_key'
+```
+
+## Example
+
+```python
+from crewai_tools import TavilyGetResearchTool
+
+tavily_get_research_tool = TavilyGetResearchTool()
+
+status_result = tavily_get_research_tool.run(
+    request_id="Your Request ID Here"
+)
+print(status_result)
+```
+
+## Arguments
+
+The `TavilyGetResearchTool` accepts the following arguments during initialization or when calling the `run` method:
+
+- `request_id` (str): Existing Tavily research request ID to retrieve.
+
+## Response Format
+
+The tool returns a JSON string containing the current research task status and any available results from Tavily.

lib/crewai-tools/src/crewai_tools/tools/tavily_get_research_tool/__init__.py

@@ -0,0 +1 @@
+

lib/crewai-tools/src/crewai_tools/tools/tavily_get_research_tool/tavily_get_research_tool.py

@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+import json
+import os
+from typing import Any
+
+from crewai.tools import BaseTool, EnvVar
+from dotenv import load_dotenv
+from pydantic import BaseModel, ConfigDict, Field, PrivateAttr
+
+
+load_dotenv()
+try:
+    from tavily import AsyncTavilyClient, TavilyClient  # type: ignore[import-untyped]
+
+    TAVILY_AVAILABLE = True
+except ImportError:
+    TAVILY_AVAILABLE = False
+
+
+class TavilyGetResearchToolSchema(BaseModel):
+    """Input schema for TavilyGetResearchTool."""
+
+    request_id: str = Field(
+        ...,
+        description="Existing Tavily research request ID to fetch status and results for.",
+    )
+
+
+class TavilyGetResearchTool(BaseTool):
+    """Tool that uses the Tavily Research status endpoint to retrieve results."""
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+    _client: Any | None = PrivateAttr(default=None)
+    _async_client: Any | None = PrivateAttr(default=None)
+    name: str = "Tavily Get Research"
+    description: str = (
+        "A tool that retrieves the status and results of an existing Tavily "
+        "research task by request ID. It returns Tavily responses as JSON."
+    )
+    args_schema: type[BaseModel] = TavilyGetResearchToolSchema
+    package_dependencies: list[str] = Field(default_factory=lambda: ["tavily-python"])
+    env_vars: list[EnvVar] = Field(
+        default_factory=lambda: [
+            EnvVar(
+                name="TAVILY_API_KEY",
+                description="API key for Tavily research service",
+                required=True,
+            ),
+        ]
+    )
+
+    def __init__(self, **kwargs: Any):
+        super().__init__(**kwargs)
+        if TAVILY_AVAILABLE:
+            api_key = os.getenv("TAVILY_API_KEY")
+            self._client = TavilyClient(api_key=api_key)
+            self._async_client = AsyncTavilyClient(api_key=api_key)
+        else:
+            try:
+                import subprocess
+
+                import click
+            except ImportError as e:
+                raise ImportError(
+                    "The 'tavily-python' package is required. 'click' and "
+                    "'subprocess' are also needed to assist with installation "
+                    "if the package is missing. Please install 'tavily-python' "
+                    "manually (e.g., 'pip install tavily-python') and ensure "
+                    "'click' and 'subprocess' are available."
+                ) from e
+
+            if click.confirm(
+                "You are missing the 'tavily-python' package, which is required "
+                "for TavilyGetResearchTool. Would you like to install it?"
+            ):
+                try:
+                    subprocess.run(["uv", "add", "tavily-python"], check=True)  # noqa: S607
+                    raise ImportError(
+                        "'tavily-python' has been installed. Please restart your "
+                        "Python application to use the TavilyGetResearchTool."
+                    )
+                except subprocess.CalledProcessError as e:
+                    raise ImportError(
+                        f"Attempted to install 'tavily-python' but failed: {e}. "
+                        "Please install it manually to use the TavilyGetResearchTool."
+                    ) from e
+            else:
+                raise ImportError(
+                    "The 'tavily-python' package is required to use the "
+                    "TavilyGetResearchTool. Please install it with: uv add tavily-python"
+                )
+
+    @staticmethod
+    def _stringify_response(response: Any) -> str:
+        if isinstance(response, str):
+            return response
+        return json.dumps(response, indent=2)
+
+    def _run(self, request_id: str) -> str:
+        """Synchronously retrieves Tavily research task status and results."""
+        if not self._client:
+            raise ValueError(
+                "Tavily client is not initialized. Ensure 'tavily-python' is "
+                "installed and API key is set."
+            )
+
+        return self._stringify_response(self._client.get_research(request_id))
+
+    async def _arun(self, request_id: str) -> str:
+        """Asynchronously retrieves Tavily research task status and results."""
+        if not self._async_client:
+            raise ValueError(
+                "Tavily async client is not initialized. Ensure 'tavily-python' is "
+                "installed and API key is set."
+            )
+
+        return self._stringify_response(
+            await self._async_client.get_research(request_id)
+        )

lib/crewai-tools/src/crewai_tools/tools/tavily_research_tool/README.md

@@ -0,0 +1,132 @@
+# Tavily Research Tool
+
+## Description
+
+The `TavilyResearchTool` provides an interface to Tavily Research through the Tavily Python SDK. It creates research tasks from an `input` prompt and can optionally stream Server-Sent Events (SSE) when `stream=True`.
+
+## Installation
+
+To use the `TavilyResearchTool`, you need to install the `tavily-python` library:
+
+```shell
+uv add 'crewai[tools]' tavily-python
+```
+
+## Environment Variables
+
+Ensure your Tavily API key is set as an environment variable:
+
+```bash
+export TAVILY_API_KEY='your_tavily_api_key'
+```
+
+## Example
+
+Here's how to initialize and use the `TavilyResearchTool` within a CrewAI agent:
+
+```python
+from crewai import Agent, Task, Crew
+from crewai_tools import TavilyResearchTool
+
+# Initialize the tool
+tavily_research_tool = TavilyResearchTool()
+
+# Create an agent that uses the tool
+researcher = Agent(
+    role="Research Analyst",
+    goal="Produce structured research reports",
+    backstory="An expert analyst who uses Tavily Research for deep web research.",
+    tools=[tavily_research_tool],
+    verbose=True,
+)
+
+# Create a task for the agent
+research_task = Task(
+    description="Research the latest developments in AI infrastructure startups.",
+    expected_output="A detailed report with citations and supporting sources.",
+    agent=researcher,
+)
+
+# Run the crew
+crew = Crew(
+    agents=[researcher],
+    tasks=[research_task],
+    verbose=2,
+)
+
+result = crew.kickoff()
+print(result)
+
+# Direct tool usage: create a structured research task
+structured_result = tavily_research_tool.run(
+    input="Research the latest developments in AI infrastructure startups.",
+    model="pro",
+    output_schema={
+        "properties": {
+            "summary": {
+                "type": "string",
+                "description": "A concise summary of the research findings",
+            },
+            "key_trends": {
+                "type": "array",
+                "description": "The major trends identified in the research",
+                "items": {"type": "string"},
+            },
+            "companies": {
+                "type": "array",
+                "description": "Notable companies mentioned in the research",
+                "items": {
+                    "type": "object",
+                    "description": "A company entry",
+                    "properties": {
+                        "name": {
+                            "type": "string",
+                            "description": "The company name",
+                        },
+                        "focus": {
+                            "type": "string",
+                            "description": "The company's main area of focus",
+                        },
+                        "notable_update": {
+                            "type": "string",
+                            "description": "A notable recent update about the company",
+                        },
+                    },
+                    "required": ["name", "focus", "notable_update"],
+                },
+            },
+        },
+        "required": ["summary", "key_trends", "companies"],
+    },
+    citation_format="apa",
+)
+print(structured_result)
+
+# Direct tool usage: stream research updates
+stream = tavily_research_tool.run(
+    input="Research the latest developments in AI infrastructure startups.",
+    model="mini",
+    stream=True,
+)
+for chunk in stream:
+    print(chunk.decode("utf-8", errors="replace"), end="")
+```
+
+## Arguments
+
+The `TavilyResearchTool` accepts the following arguments during initialization or when calling the `run` method:
+
+- `input` (str): The research task or question to investigate.
+- `model` (Literal["mini", "pro", "auto"], optional): The Tavily research model to use. Defaults to `"auto"`.
+- `output_schema` (dict[str, Any], optional): A JSON Schema used to structure the research output. Tavily expects top-level `properties` and optional `required` keys, and each property should include a `description`.
+- `stream` (bool, optional): Whether to return Tavily's streaming SSE chunk generator. Defaults to `False`.
+- `citation_format` (Literal["numbered", "mla", "apa", "chicago"], optional): Citation format for the report. Defaults to `"numbered"`.
+
+## Response Format
+
+The tool returns:
+
+- A JSON string when creating a non-streaming research task
+- A byte generator of SSE chunks when `stream=True`
+
+Refer to the Tavily Research API documentation for the full response structure and streaming event format.

lib/crewai-tools/src/crewai_tools/tools/tavily_research_tool/tavily_research_tool.py

@@ -0,0 +1,200 @@
+from __future__ import annotations
+
+from collections.abc import AsyncGenerator, Generator
+import json
+import os
+from typing import Any, Literal, cast
+
+from crewai.tools import BaseTool, EnvVar
+from dotenv import load_dotenv
+from pydantic import BaseModel, ConfigDict, Field, PrivateAttr
+
+
+load_dotenv()
+try:
+    from tavily import (  # type: ignore[import-untyped, import-not-found, unused-ignore]
+        AsyncTavilyClient,
+        TavilyClient,
+    )
+
+    TAVILY_AVAILABLE = True
+except ImportError:
+    TAVILY_AVAILABLE = False
+
+
+class TavilyResearchToolSchema(BaseModel):
+    """Input schema for TavilyResearchTool."""
+
+    input: str = Field(
+        ...,
+        description="The research task or question to investigate.",
+    )
+    model: Literal["mini", "pro", "auto"] = Field(
+        default="auto",
+        description="The model used by the Tavily research agent.",
+    )
+    output_schema: dict[str, Any] | None = Field(
+        default=None,
+        description="Optional JSON Schema that structures the research output.",
+    )
+    stream: bool = Field(
+        default=False,
+        description="Whether to stream research progress and results as SSE chunks.",
+    )
+    citation_format: Literal["numbered", "mla", "apa", "chicago"] = Field(
+        default="numbered",
+        description="Citation format for the research report.",
+    )
+
+
+class TavilyResearchTool(BaseTool):
+    """Tool that uses the Tavily Research API to create research tasks."""
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+    _client: Any | None = PrivateAttr(default=None)
+    _async_client: Any | None = PrivateAttr(default=None)
+    name: str = "Tavily Research"
+    description: str = (
+        "A tool that creates Tavily research tasks and can stream research "
+        "progress and results. It returns Tavily responses as JSON or SSE chunks."
+    )
+    args_schema: type[BaseModel] = TavilyResearchToolSchema
+    model: Literal["mini", "pro", "auto"] = Field(
+        default="auto",
+        description="Default model used for new Tavily research tasks.",
+    )
+    output_schema: dict[str, Any] | None = Field(
+        default=None,
+        description="Default JSON Schema used to structure research output.",
+    )
+    stream: bool = Field(
+        default=False,
+        description="Whether new Tavily research tasks should stream responses by default.",
+    )
+    citation_format: Literal["numbered", "mla", "apa", "chicago"] = Field(
+        default="numbered",
+        description="Default citation format for Tavily research results.",
+    )
+    package_dependencies: list[str] = Field(default_factory=lambda: ["tavily-python"])
+    env_vars: list[EnvVar] = Field(
+        default_factory=lambda: [
+            EnvVar(
+                name="TAVILY_API_KEY",
+                description="API key for Tavily research service",
+                required=True,
+            ),
+        ]
+    )
+
+    def __init__(self, **kwargs: Any):
+        super().__init__(**kwargs)
+        if TAVILY_AVAILABLE:
+            api_key = os.getenv("TAVILY_API_KEY")
+            self._client = TavilyClient(api_key=api_key)
+            self._async_client = AsyncTavilyClient(api_key=api_key)
+        else:
+            try:
+                import subprocess
+
+                import click
+            except ImportError as e:
+                raise ImportError(
+                    "The 'tavily-python' package is required. 'click' and "
+                    "'subprocess' are also needed to assist with installation "
+                    "if the package is missing. Please install 'tavily-python' "
+                    "manually (e.g., 'pip install tavily-python') and ensure "
+                    "'click' and 'subprocess' are available."
+                ) from e
+
+            if click.confirm(
+                "You are missing the 'tavily-python' package, which is required "
+                "for TavilyResearchTool. Would you like to install it?"
+            ):
+                try:
+                    subprocess.run(["uv", "add", "tavily-python"], check=True)  # noqa: S607
+                    raise ImportError(
+                        "'tavily-python' has been installed. Please restart your "
+                        "Python application to use the TavilyResearchTool."
+                    )
+                except subprocess.CalledProcessError as e:
+                    raise ImportError(
+                        f"Attempted to install 'tavily-python' but failed: {e}. "
+                        "Please install it manually to use the TavilyResearchTool."
+                    ) from e
+            else:
+                raise ImportError(
+                    "The 'tavily-python' package is required to use the "
+                    "TavilyResearchTool. Please install it with: uv add tavily-python"
+                )
+
+    @staticmethod
+    def _stringify_response(response: Any) -> str:
+        if isinstance(response, str):
+            return response
+        return json.dumps(response, indent=2)
+
+    def _run(
+        self,
+        input: str,
+        model: Literal["mini", "pro", "auto"] | None = None,
+        output_schema: dict[str, Any] | None = None,
+        stream: bool | None = None,
+        citation_format: Literal["numbered", "mla", "apa", "chicago"] | None = None,
+    ) -> str | Generator[bytes, None, None]:
+        """Synchronously creates Tavily research tasks or streams results."""
+        if not self._client:
+            raise ValueError(
+                "Tavily client is not initialized. Ensure 'tavily-python' is "
+                "installed and API key is set."
+            )
+
+        use_stream = self.stream if stream is None else stream
+        result = self._client.research(
+            input=input,
+            model=self.model if model is None else model,
+            output_schema=self.output_schema
+            if output_schema is None
+            else output_schema,
+            stream=use_stream,
+            citation_format=(
+                self.citation_format if citation_format is None else citation_format
+            ),
+        )
+
+        if use_stream:
+            return cast(Generator[bytes, None, None], result)
+
+        return self._stringify_response(result)
+
+    async def _arun(
+        self,
+        input: str,
+        model: Literal["mini", "pro", "auto"] | None = None,
+        output_schema: dict[str, Any] | None = None,
+        stream: bool | None = None,
+        citation_format: Literal["numbered", "mla", "apa", "chicago"] | None = None,
+    ) -> str | AsyncGenerator[bytes, None]:
+        """Asynchronously creates Tavily research tasks or streams results."""
+        if not self._async_client:
+            raise ValueError(
+                "Tavily async client is not initialized. Ensure 'tavily-python' is "
+                "installed and API key is set."
+            )
+
+        use_stream = self.stream if stream is None else stream
+        result = await self._async_client.research(
+            input=input,
+            model=self.model if model is None else model,
+            output_schema=self.output_schema
+            if output_schema is None
+            else output_schema,
+            stream=use_stream,
+            citation_format=(
+                self.citation_format if citation_format is None else citation_format
+            ),
+        )
+
+        if use_stream:
+            return cast(AsyncGenerator[bytes, None], result)
+
+        return self._stringify_response(result)

lib/crewai-tools/src/crewai_tools/tools/tavily_search_tool/README.md

@@ -9,7 +9,7 @@ The `TavilySearchTool` provides an interface to the Tavily Search API, enabling
 To use the `TavilySearchTool`, you need to install the `tavily-python` library:
 
 ```shell
-pip install 'crewai[tools]' tavily-python
+uv add 'crewai[tools]' tavily-python
 ```
 
 ## Environment Variables

lib/crewai-tools/tool.specs.json

@@ -25039,6 +25039,243 @@
         "type": "object"
       }
     },
+    {
+      "description": "A tool that retrieves the status and results of an existing Tavily research task by request ID. It returns Tavily responses as JSON.",
+      "env_vars": [
+        {
+          "default": null,
+          "description": "API key for Tavily research service",
+          "name": "TAVILY_API_KEY",
+          "required": true
+        }
+      ],
+      "humanized_name": "Tavily Get Research",
+      "init_params_schema": {
+        "$defs": {
+          "EnvVar": {
+            "properties": {
+              "default": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "default": null,
+                "title": "Default"
+              },
+              "description": {
+                "title": "Description",
+                "type": "string"
+              },
+              "name": {
+                "title": "Name",
+                "type": "string"
+              },
+              "required": {
+                "default": true,
+                "title": "Required",
+                "type": "boolean"
+              }
+            },
+            "required": [
+              "name",
+              "description"
+            ],
+            "title": "EnvVar",
+            "type": "object"
+          }
+        },
+        "description": "Tool that uses the Tavily Research status endpoint to retrieve results.",
+        "properties": {},
+        "required": [],
+        "title": "TavilyGetResearchTool",
+        "type": "object"
+      },
+      "name": "TavilyGetResearchTool",
+      "package_dependencies": [
+        "tavily-python"
+      ],
+      "run_params_schema": {
+        "description": "Input schema for TavilyGetResearchTool.",
+        "properties": {
+          "request_id": {
+            "description": "Existing Tavily research request ID to fetch status and results for.",
+            "title": "Request Id",
+            "type": "string"
+          }
+        },
+        "required": [
+          "request_id"
+        ],
+        "title": "TavilyGetResearchToolSchema",
+        "type": "object"
+      }
+    },
+    {
+      "description": "A tool that creates Tavily research tasks and can stream research progress and results. It returns Tavily responses as JSON or SSE chunks.",
+      "env_vars": [
+        {
+          "default": null,
+          "description": "API key for Tavily research service",
+          "name": "TAVILY_API_KEY",
+          "required": true
+        }
+      ],
+      "humanized_name": "Tavily Research",
+      "init_params_schema": {
+        "$defs": {
+          "EnvVar": {
+            "properties": {
+              "default": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "default": null,
+                "title": "Default"
+              },
+              "description": {
+                "title": "Description",
+                "type": "string"
+              },
+              "name": {
+                "title": "Name",
+                "type": "string"
+              },
+              "required": {
+                "default": true,
+                "title": "Required",
+                "type": "boolean"
+              }
+            },
+            "required": [
+              "name",
+              "description"
+            ],
+            "title": "EnvVar",
+            "type": "object"
+          }
+        },
+        "description": "Tool that uses the Tavily Research API to create research tasks.",
+        "properties": {
+          "citation_format": {
+            "default": "numbered",
+            "description": "Default citation format for Tavily research results.",
+            "enum": [
+              "numbered",
+              "mla",
+              "apa",
+              "chicago"
+            ],
+            "title": "Citation Format",
+            "type": "string"
+          },
+          "model": {
+            "default": "auto",
+            "description": "Default model used for new Tavily research tasks.",
+            "enum": [
+              "mini",
+              "pro",
+              "auto"
+            ],
+            "title": "Model",
+            "type": "string"
+          },
+          "output_schema": {
+            "anyOf": [
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "description": "Default JSON Schema used to structure research output.",
+            "title": "Output Schema"
+          },
+          "stream": {
+            "default": false,
+            "description": "Whether new Tavily research tasks should stream responses by default.",
+            "title": "Stream",
+            "type": "boolean"
+          }
+        },
+        "required": [],
+        "title": "TavilyResearchTool",
+        "type": "object"
+      },
+      "name": "TavilyResearchTool",
+      "package_dependencies": [
+        "tavily-python"
+      ],
+      "run_params_schema": {
+        "description": "Input schema for TavilyResearchTool.",
+        "properties": {
+          "citation_format": {
+            "default": "numbered",
+            "description": "Citation format for the research report.",
+            "enum": [
+              "numbered",
+              "mla",
+              "apa",
+              "chicago"
+            ],
+            "title": "Citation Format",
+            "type": "string"
+          },
+          "input": {
+            "description": "The research task or question to investigate.",
+            "title": "Input",
+            "type": "string"
+          },
+          "model": {
+            "default": "auto",
+            "description": "The model used by the Tavily research agent.",
+            "enum": [
+              "mini",
+              "pro",
+              "auto"
+            ],
+            "title": "Model",
+            "type": "string"
+          },
+          "output_schema": {
+            "anyOf": [
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "default": null,
+            "description": "Optional JSON Schema that structures the research output.",
+            "title": "Output Schema"
+          },
+          "stream": {
+            "default": false,
+            "description": "Whether to stream research progress and results as SSE chunks.",
+            "title": "Stream",
+            "type": "boolean"
+          }
+        },
+        "required": [
+          "input"
+        ],
+        "title": "TavilyResearchToolSchema",
+        "type": "object"
+      }
+    },
     {
       "description": "A tool that performs web searches using the Tavily Search API. It returns a JSON object containing the search results.",
       "env_vars": [

uv.lock

@@ -13,7 +13,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-04-27T16:00:00Z"
+exclude-newer = "2026-04-28T07:00:00Z"
 
 [manifest]
 members = [
@@ -1660,7 +1660,7 @@ requires-dist = [
     { name = "sqlalchemy", marker = "extra == 'singlestore'", specifier = ">=2.0.40" },
     { name = "sqlalchemy", marker = "extra == 'sqlalchemy'", specifier = ">=2.0.35" },
     { name = "stagehand", marker = "extra == 'stagehand'", specifier = ">=0.4.1" },
-    { name = "tavily-python", marker = "extra == 'tavily-python'", specifier = ">=0.5.4" },
+    { name = "tavily-python", marker = "extra == 'tavily-python'", specifier = "~=0.7.14" },
     { name = "tiktoken", specifier = ">=0.8.0,<0.13" },
     { name = "unstructured", extras = ["all-docs", "local-inference"], marker = "extra == 'xml'", specifier = ">=0.17.2" },
     { name = "weaviate-client", marker = "extra == 'weaviate-client'", specifier = ">=4.10.2" },