MCP servers and skills: search, filter by where they run, and compare.
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector sear
OfficialSkillMIT★ 1.6k in collectionNo key
Caelune (凯露恩) — Local-first retrieval for private Markdown, PDF, and Tika documents, with a Windows desktop app and read-only MCP server.｜本地优先的私人知识检索工具。
SkillMIT★ 45No key
MCP Documentation Server - Bridge the AI Knowledge Gap. ✨ Features: Document management • Gemini integration • AI-powered semantic search • File uploads • Smart chunking • Multilingual support • Zero-
Node.jsMIT★ 343No key
Hybrid search for Obsidian vaults via plugin, CLI, and MCP server
Node.jsMIT★ 111No key
Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple Silicon.. No Server. No API. One File. Pure Swift
SkillApache-2.0★ 804No key
Four local, file-based MCP servers for solo devs/vibecoders: persistent memory, session handoff/resume, file checkpoints, token-efficient project briefings. Works with any MCP client.
Node.jsMIT★ 96No key
Karpathy's LLM Wiki idea as a product — an AI that builds and maintains a markdown wiki from your notes and sources. MCP server + web UI, runs on free local models (Ollama), no API key needed. MIT.
Node.jsMIT★ 130No key
A local dual-layer memory pattern for AI agents: a compact, human-readable markdown index paired with semantic retrieval from a local vector store, queried before each message. For cross-project recal
SkillApache-2.0★ 63No key
Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sources with citations.
SkillMIT★ 116No key
PythonAGPL-3.0★ 29No key
Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST API and MCP support for AI clients.
Node.jsMIT★ 115No key
Cursor-style semantic code search as an MCP plugin for Claude Code. Instead of grepping 50 files and sending 30,000 tokens to Claude, VecGrep returns the top 8 semantically relevant code chunks (~1,60
PythonMIT★ 9No key
Local code search combining BM25, vector similarity, and cross-encoder reranking. Parses 60+ languages with tree-sitter, runs entirely offline, and returns structured results with file paths, line ran
SkillMIT★ 120No key
TypeScript RAG toolkit for semantic search, multi-provider LLM Q&A, and document APIs.
Node.jsMIT★ 1Few starsNo key
Official Findings of EMNLP 2026 implementation of Corpus2Skill: compile a document corpus into a navigable skill hierarchy that LLM agents explore at query time, with document lookup instead of a serv
SkillMIT★ 95No key
Local knowledge graph for AI agents. Hybrid search + MCP server for Obsidian vaults.
SkillMIT★ 170No key
Omnex is not a search tool. It is the memory substrate for the agentic era — the data layer that sits beneath AI agents, AI operating systems, and human-AI interaction. What exists today (file systems
SkillAGPL-3.0★ 4Few starsNo key
Obsidian plugin that runs a local MCP server, exposing vault semantic search and file operations to AI assistants.
SkillAGPL-3.0★ 14No key
Local-first second brain with semantic search. Stores notes as Markdown files and indexes them with a local ML model — no cloud, no API keys.
Node.jsMIT★ 3Few starsNo key
LegalContext is an open-source Model Context Protocol (MCP) server that creates a secure, standardized bridge between law firms' document management systems (specifically Clio) and AI assistants (star
Node.jsMPL-2.0★ 29No key
SkillMIT★ 7No key
Local-first, LLM-agnostic memory system — hybrid retrieval (vector + lexical + graph), multi-signal ranking. Runs on 4GB RAM, CPU-only, no cloud.
SkillMIT★ 15No key
PythonMIT★ 2Few starsNo key
Go port of echovault: Local-first memory for coding agents. Decisions, bugs, and context stored as Markdown, indexed locally with FTS5 plus optional semantic search. No RAM overhead at idle, no extern
DockerMIT★ 4Few starsNo key
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