Discover our curated collection of MCP servers for database management. Browse 1975 servers and find the perfect MCPs for your needs.
Enables Claude to execute SQL queries and interact with Snowflake databases.
Facilitates database interactions with ArangoDB through a Model Context Protocol (MCP) server.
Enables interaction with MSSQL databases, facilitating SQL query execution and business intelligence tasks.
Enables seamless integration between MCP clients and Supabase services such as databases, storage, and edge functions.
Enables interaction with Salesforce through its REST API using the Model Context Protocol.
Connects LLMs to Databricks, enabling natural language interaction with SQL warehouses and job management.
Provides access to Kuzu databases for Large Language Models (LLMs) by enabling schema inspection and query execution.
Enables AI assistants to execute SQL queries against AWS Athena databases and retrieve results.
Provides vector database capabilities through Chroma for semantic document search and management.
Enables natural language interaction with Apache Iceberg lakehouses through a Model Context Protocol (MCP) server.
Enables LLM models to interact with Apache Kafka through the Model Context Protocol (MCP).
Eases LLM integration with Dremio through a Model Context Protocol server.
Provides tools for interacting with Teradata databases, including query execution, DDL retrieval, database/table listing, and data quality analysis.
Provides an advanced MCP server for RAG-enabled memory, leveraging a knowledge graph with vector search capabilities.
Enables AI assistants to interact with over 200 database types by integrating with DBeaver's existing connections.
Enables AI agents to discover, access, and query high-quality business data products while enforcing data governance policies.
Provides a production-ready Model Context Protocol (MCP) server for AI agents to store, retrieve, and manage semantic memory and contextual knowledge across sessions.
Integrates Slack data in real-time to power agentic AI assistants with conversational memory.
Enables agentic AI applications to interact with IBM i systems through a robust Model Context Protocol (MCP) server.
Extends PostgreSQL with advanced vector search, machine learning algorithms, and agent runtime capabilities.
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