什么是 #retrieval MCP 服务器?
标记为 #retrieval 的 MCP 服务器实现了 Model Context Protocol,让 Claude、Cursor、VS Code 等 AI 助手可以访问 retrieval 相关的工具、数据或 API。
以下 MCP 服务器和客户端均标记为 #retrieval——安装后即可让 Claude、Cursor、VS Code 等支持 MCP 的客户端获得 retrieval 相关能力。
Lochless
Every match, not the top 10. Lochless is a hosted text index for LLM apps and agents. Send raw text through the API, then ask in plain English. It reads the documents in scope, up to a read limit you set, and returns eve
roomi-fields
The open retrieval layer for AI coding agents. Indexes code, docs, legal, research, data — 15 parsers, FTS5 + semantic search, knowledge graph. Serves surgical context via MCP. Open source, local, free.
MoAz06
The agent only answers from a page it actually read.
ndjordjevic
PinRAG is a retrieval-augmented generation (RAG) MCP server built with LangChain and Chroma. Index PDFs, plain text, Discord exports, YouTube transcripts, and GitHub repositories, then ask questions in Cursor, VS Code (Copilot), or any MCP-capable client. Answers include citation
maxbaluev
AccInt is a local Work Model and MCP server for persistent scored agent memory, retrieval, commitments, browser/runtime observations, and outcome-based learning across coding agents.
tijuthomas5
Local-first code retrieval for AI agents — cuts codebase context from tens of thousands of tokens to a few hundred, with zero hallucinated file paths.
supermaxlol
Cognitive memory system for AI agents with 129 MCP tools. Persistent hierarchical memory, emotional recall, knowledge graphs, spreading activation, hybrid retrieval (BM25+RRF), metacognition, goal tracking, spaced repetition, dream consolidation, and more.
VoxellInc
Forge is Voxell's hosted text-embedding API. This MCP server exposes two tools — embed (turn text into vectors) and list_models — so any MCP-compatible agent can generate embeddings for semantic search, RAG, clustering, and dedup.
mrlynn
MCP server for Voyage AI embeddings, reranking, and MongoDB Atlas Vector Search. Provides 11 tools for semantic search, document ingestion, cost estimation, and model exploration. Full RAG pipeline: chunk, embed, vector search, and rerank from any MCP client.
HaseebKhalid1507
关于 #retrieval 标签下 MCP 服务器和客户端的常见问题
标记为 #retrieval 的 MCP 服务器实现了 Model Context Protocol,让 Claude、Cursor、VS Code 等 AI 助手可以访问 retrieval 相关的工具、数据或 API。
mcp.so 目前收录了 10 个标记为 #retrieval 的 MCP 服务器和客户端。
打开下方任意服务器页面,将安装配置复制到 Claude Desktop、Cursor、VS Code 或其他 MCP 客户端的配置中即可——远程服务器无需单独下载。