MCPs tagged with # Semantic Search

Web Analyzer MCP is an MCP-compliant server designed for intelligent web content analysis and summarization. It leverages FastMCP to perform advanced web scraping, content extraction, and AI-powered question-answering using OpenAI models. The tool integrates with various developer IDEs, offering structured markdown output, essential content extraction, and smart Q&A functionality. Its features streamline content analysis workflows and support flexible model selection.

• ⭐ 2
• MCP
• kimdonghwi94/web-analyzer-mcp

Trieve offers a platform for semantic search, recommendations, and retrieval-augmented generation (RAG). It supports dense vector search, typo-tolerant neural search, sub-sentence highlighting, and integrates with a variety of embedding models. Trieve can be self-hosted and features APIs for context management with LLMs, including Bring Your Own Model and managed RAG endpoints. Full documentation and SDKs are available for streamlined integration.

• ⭐ 2,555
• MCP
• devflowinc/trieve

MCP Local RAG is a privacy-preserving, local document search server designed for use with Model Context Protocol (MCP) clients such as Cursor, Codex, and Claude Code. It enables users to ingest and semantically search local documents without using external APIs or cloud services. All processing, including embedding generation and vector storage, is performed on the user's machine. The tool supports document ingestion, semantic search, file management, file deletion, and system status reporting through MCP.

• ⭐ 10
• MCP
• shinpr/mcp-local-rag

In Memoria is an MCP server that enables AI coding assistants such as Claude or Copilot to retain, recall, and provide context about codebases across sessions. It learns patterns, architecture, and conventions from user code, offering persistent intelligence that eliminates repetitive explanations and generic suggestions. Through the Model Context Protocol, it allows AI tools to perform semantic search, smart file routing, and track project-specific decisions efficiently.

• ⭐ 94
• MCP
• pi22by7/In-Memoria

Mem0 MCP Server implements a Model Context Protocol-compliant server for storing, retrieving, and searching coding preferences. It integrates with Mem0 and offers tools for persistent management of code snippets, best practices, and technical documentation. The server exposes an SSE endpoint for clients like Cursor, enabling seamless access and interaction with coding context data.

• ⭐ 506
• MCP
• mem0ai/mem0-mcp

RAG Documentation MCP Server provides vector-based search and retrieval tools for documentation, enabling large language models to reference relevant context in their responses. It supports managing multiple documentation sources, semantic search, and real-time context delivery. Documentation can be indexed, searched, and managed with queueing and processing features, making it highly suitable for AI-driven assistants. Integration with Claude Desktop and support for Qdrant vector databases is also available.

• ⭐ 238
• MCP
• hannesrudolph/mcp-ragdocs

Sourcerer MCP provides a Model Context Protocol (MCP) server that enables AI agents to perform semantic code search and navigation. By indexing codebases at the function, class, and chunk level, it allows agents to retrieve only the necessary code snippets, greatly reducing token consumption. The tool integrates with Tree-sitter for language parsing and OpenAI for generating code embeddings, supporting advanced contextual code understanding without full file ingestion.

• ⭐ 95
• MCP
• st3v3nmw/sourcerer-mcp

The Vercel AI SDK Documentation MCP Agent is a server implementing the Model Context Protocol to enable AI-powered search and conversational querying of the Vercel AI SDK documentation. It features natural language understanding, semantic search using FAISS, and session-based context management for in-depth assistance. Integration with popular MCP clients like Claude Desktop and Cursor ensures seamless use in developer workflows. Automated documentation indexing and a Gemini-powered agent enhance accuracy and contextuality of responses.

• ⭐ 41
• MCP
• IvanAmador/vercel-ai-docs-mcp

Rust Docs MCP Server provides AI coding assistants with a focused tool to query current documentation for specific Rust crates. It runs as a standard MCP server over stdio, enabling context-driven semantic searches and LLM-generated answers based only on retrieved documentation. It fetches crate docs, generates embeddings, and leverages OpenAI APIs for accurate and relevant code support, with support for caching and multi-crate operation.

• ⭐ 208
• MCP
• Govcraft/rust-docs-mcp-server

mcp-pinecone implements a Model Context Protocol (MCP) server that integrates with Pinecone indexes for use with clients such as Claude Desktop. It provides powerful tools for semantic search, document reading, listing, and processing within a Pinecone vector database. The server supports operations like embedding, chunking, and upserting records, enabling contextual management of large document sets. Designed for ease of installation and interoperability via the MCP standard.

• ⭐ 150
• MCP
• sirmews/mcp-pinecone

memvid-mcp-server provides a Model Context Protocol (MCP) compatible HTTP server that leverages memvid to encode text data into videos. It supports adding text chunks as video and performing semantic search over them using standardized MCP actions such as add_chunks and search. The server can be integrated with MCP clients via streamable HTTP and enables fast context retrieval for AI applications.

• ⭐ 8
• MCP
• ferrants/memvid-mcp-server

Chroma MCP Server implements the Model Context Protocol to allow seamless integration between LLM applications and external data using the Chroma embedding database. It enables AI models to create, manage, and query collections with advanced vector search, full text search, and metadata filtering. The server supports both ephemeral and persistent client types, along with integration for HTTP and cloud-based Chroma instances. Multiple embedding functions, collection management tools, and rich document operations are available for extensible LLM workflows.

• ⭐ 418
• MCP
• chroma-core/chroma-mcp

CICADA is an MCP server that provides AI assistants with AST-level, structured access to Elixir codebases. It enables code analysis, semantic search, module and function discovery, and git/PR attribution for deeper contextual understanding. CICADA supports multiple editors and offers features like dependency mapping, dead-code detection, and local indexing with strong privacy guarantees.

• ⭐ 11
• MCP
• wende/cicada

Serena is a free and open-source coding agent toolkit that enhances large language models with advanced semantic code retrieval and editing tools. It enables integration through the Model Context Protocol (MCP), allowing seamless operation with various coding agents, IDEs, and interfaces. Serena extracts code entities at the symbol level, supports context-aware operations, and improves token efficiency for coding tasks. The tools can be incorporated into diverse LLM-driven environments for more efficient and precise code editing.

• ⭐ 15,643
• MCP
• oraios/serena

FHIR MCP Server implements a full Model Context Protocol server, enabling large language model agents to perform comprehensive CRUD operations on FHIR-compliant healthcare data. It offers standardized integration with various clinical data sources, natural-language query capabilities, and supports secure authentication via OAuth2. The server includes semantic search, AI-powered document processing, terminology resolution, Docker deployment, and is optimized for use with MCP-compatible clients like Claude Desktop.

• ⭐ 34
• MCP
• the-momentum/fhir-mcp-server