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Overview

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These tools enable your agents to interact with various database systems, from traditional SQL databases to modern vector stores and data warehouses.

Available Tools

MySQL Tool

Connect to and query MySQL databases with SQL operations.

PostgreSQL Search

Search and query PostgreSQL databases efficiently.

Snowflake Search

Access Snowflake data warehouse for analytics and reporting.

NL2SQL Tool

Convert natural language queries to SQL statements automatically.

Qdrant Vector Search

Search vector embeddings using Qdrant vector database.

Weaviate Vector Search

Perform semantic search with Weaviate vector database.

MongoDB Vector Search

Vector similarity search on MongoDB Atlas with indexing helpers.

SingleStore Search

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
from crewai_tools import MySQLTool, MongoDBVectorSearchTool, QdrantVectorSearchTool, NL2SQLTool

# Create database tools
mysql_db = MySQLTool()
mongodb_vector_search = MongoDBVectorSearchTool(
    connection_string="<MONGODB_URI>",
    database_name="<database>",
    collection_name="<collection>",
)
qdrant_vector_search = QdrantVectorSearchTool()
nl_to_sql = NL2SQLTool()

# Add to your agent
agent = Agent(
    role="Data Analyst",
    tools=[mysql_db, mongodb_vector_search, qdrant_vector_search, nl_to_sql],
    goal="Extract insights from various data sources"
)
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