Model Context Protocol
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A Model Context Protocol server that provides MySQL database operations. This server enables AI models to interact with MySQL databases through a standardized interface.
A Model Context Protocol (MCP) server implementation that provides Elasticsearch interaction. This server enables searching documents, analyzing indices, and managing cluster through a set of tools.
Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases
A Model Context Protocol server that provides read-only access to PostgreSQL databases. This server enables LLMs to inspect database schemas and execute read-only queries.
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A Model Context Protocol server that provides MySQL database operations. This server enables AI models to interact with MySQL databases through a standardized interface.
Model Context Protocol with Neo4j. This server provides natural language interaction with Neo4j and Aura accounts.
Model Context Protocol server to allow for reading and writing from Pinecone. Rudimentary RAG
A Model Context Protocol (MCP) server implementation for DuckDB, providing database interaction capabilities through MCP tools.
A mongo db server for the model context protocol (MCP)
Supabase MCP Server enabling Cursor & Windsurf to use any method from Management API and query your database
an mcp server for vikingdb store and search
Understanding Model Context Protocol (MCP)
Model Context Protocol (MCP) is a groundbreaking open-source protocol developed by Anthropic that revolutionizes how AI systems interact with external data sources. As the foundation for next-generation AI interactions, MCP enables AI assistants like Claude to establish secure and standardized connections with various data sources and tools.
Key Features of MCP
- Universal Standard: Provides a unified framework for AI systems to access external data, tools, and prompts
- Client-Server Architecture: Implements a robust and scalable architecture for seamless AI interactions
- Security-First Design: Ensures secure data transmission and access control between AI systems and data sources
- Tool Integration: Enables AI assistants to interact with various external tools and services
- Standardized Communication: Establishes consistent protocols for data exchange and interaction patterns
Benefits for AI Development
MCP represents a significant advancement in AI infrastructure, offering developers and organizations a standardized way to build and deploy AI applications. By providing a common protocol, MCP reduces implementation complexity and ensures compatibility across different AI systems and data sources.
Whether you're developing AI applications, managing data infrastructure, or implementing AI solutions, MCP provides the foundation for secure, efficient, and standardized AI interactions. Explore our directory to find MCP servers that match your specific needs and requirements.