The Excellence
Directory Platform Template

A Pinecone MCP server providing vector search capabilities over Pinecone through the Model Context Protocol.

Provides up-to-date documentation context for a specific Rust crate to LLMs via an MCP tool, using semantic search and LLM summarization.

An MCP server providing semantic data search using embeddings and similarity matching. Facilitates AI-powered, context-aware data retrieval for development teams.

A server providing data retrieval capabilities powered by the Chroma embedding database, enabling AI models to create and retrieve data collections using vector search, full text search, and metadata filtering.

Combines Neo4j and Qdrant databases for document search with semantic relevance and context, serving as a powerful MCP server for structured and vector search.

MCP server implementation for Alibaba Cloud Tablestore, supporting document management, semantic and vector search, RAG-friendly, and serverless capabilities.

Elasticsearch provides MCP server capabilities enabling LLMs and other clients to interact with Elasticsearch clusters for managing indices and executing search queries using natural language, demonstrating a powerful MCP server integration. Several MCP server implementations exist to facilitate semantic and natural language search with Elasticsearch, including cr7258/elasticsearch-mcp-server, elastic-semantic-search-server, Elasticsearch Mcp, Elasticsearch Server, and Elasticsearch7 Server.

A purpose-built MCP server that enables semantic data retrieval via vector embeddings, allowing AI systems to perform meaning-based searches in large datasets. Qdrant is a leading example, offering standard protocols for vector operations.

An MCP server enabling access and search functionality for local Apple Notes databases, fitting into the MCP server ecosystem. Also supports semantic search and AI-assisted Retrieval Augmented Generation (RAG) over Apple Notes, supporting secure, local interaction through Claude Desktop.

Provides a local vector database system for semantic code search with zero-configuration setup and real-time file monitoring via MCP. Relevant as an MCP server solution.

The official MCP Server for Pinecone, enabling multi-tenant vector search and privacy-safe personalization within the MCP ecosystem.

The Qdrant MCP Server integrates with the Qdrant vector search engine, allowing AI agents to store and retrieve semantic information using MCP, ideal for advanced AI memory and retrieval tasks.