--- title: "Overview" description: "Connect to databases, vector stores, and data warehouses for comprehensive data access" icon: "face-smile" --- These tools enable your agents to interact with various database systems, from traditional SQL databases to modern vector stores and data warehouses. ## **Available Tools** Connect to and query MySQL databases with SQL operations. Search and query PostgreSQL databases efficiently. Access Snowflake data warehouse for analytics and reporting. Convert natural language queries to SQL statements automatically. Search vector embeddings using Qdrant vector database. Perform semantic search with Weaviate vector database. Vector similarity search on MongoDB Atlas with indexing helpers. Safe SELECT/SHOW queries on SingleStore with pooling and validation. ## **Common Use Cases** - **Data Analysis**: Query databases for business intelligence and reporting - **Vector Search**: Find similar content using semantic embeddings - **ETL Operations**: Extract, transform, and load data between systems - **Real-time Analytics**: Access live data for decision making ```python from crewai_tools import MySQLTool, QdrantVectorSearchTool, NL2SQLTool # Create database tools mysql_db = MySQLTool() vector_search = QdrantVectorSearchTool() nl_to_sql = NL2SQLTool() # Add to your agent agent = Agent( role="Data Analyst", tools=[mysql_db, vector_search, nl_to_sql], goal="Extract insights from various data sources" )