#semantic-search

Identity, memory & collaboration platform for AI agents — facts, memories, secrets, and inter-agent messaging via a CLI, MCP, and a Go server.

Local knowledge base for coding agents with a Rust CLI/TUI, PostgreSQL storage, and optional background capture.

👀 Semantic search over PDF, Markdown, and source code; chunks and indexes files into AI embeddings in a vector database for meaning-based search.

Encrypted, fully offline agentic memory. One click install, GUI w/ memory map, all OS and agents. Superior memory creation, storage and retrieval.

SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.

Self-hosted MCP server to index and search any documentation site—public or private

Local-first MCP server for AI-powered codebase intelligence — AST analysis, dependency graphs, and semantic search. Your source code never leaves your machine.

.NET library for on-demand local AI model inference — zero bundled models, lazy loading, hardware-aware GPU/CPU selection, 10 task types including embeddings, generation, vision, and audio.

Compiles git-backed markdown into a verifiable, read-optimized index for AI coding agents.

Deep code indexing MCP server for AI agents. 25 tools: hybrid FTS5 + embedding search, call graphs, git blame/hotspots, build system analysis. Multi-repo workspaces, GPU-accelerated semantic search, 10 languages via tree-sitter. Fully local, zero cloud dependencies.

Persistent memory MCP server for AI agents — Rust, 19 tools, knowledge graph, Hebbian learning, episodic memory, contradiction detection, prospective triggers, Bayesian calibration, zero-config Docker setup.

Semantic + structural code search for AI-native development

A memory of the codebase your AI agent can't get from grep: a persistent call graph, semantic search, and per-symbol review learnings over any repo. Self-hosted MCP server — Go, tree-sitter, Apache AGE.

Local code intelligence MCP server and CLI for AI coding agents

CodeGraph builds a semantic graph of your codebase — functions, classes, imports, call chains — and exposes it through 42 MCP tools, 38 languages, a VS Code extension, and a persistent memory layer. AI agents get structured code understanding instead of grepping through files.

Search code and feature records by meaning through the command line or Model Context Protocol (MCP). Inference runs on your GPU.

Persistent memory for AI agents

Declarative SQL query engine for Qdrant and edge vector databases. Multi-vector dense & BM25 sparse search, hybrid retrieval, CTEs, and MMR in Rust, Python, Node.js, and WebAssembly

Semantic memory for AI agents — local-first MCP server with hybrid search, governance, and consolidation

Self-hosted MCP server that makes your Obsidian/markdown vault searchable — text, PDFs, Office docs, images, audio — from any MCP client. Hybrid retrieval over a typed, governed corpus, sub-second at 50k notes; your files stay plain markdown.

Local‑first MCP server for multi‑repository semantic code search with Qdrant and llama. Turns your entire workspace into private context for AI coding assistants like Claude Code, Codex, Cursor, Copilot, Antigravity and Windsurf.

공공데이터 덕후, 오데덕. AI 에이전트가 목표에 맞는 자료를 찾고, 자동 활용신청·수집·연결·분석을 거쳐 결과와 근거를 만들도록 돕는 오픈소스 실행 플랫폼.

Self-hosted open-source backend for community & social apps (posts, comments, reactions, follows, spaces, realtime chat, semantic search). API-compatible with the Replyke SDK. Built on Supabase.

Self-hosted retrieval infrastructure for AI assistants. MCP-first search and grounded answers over a private corpus, with citations that resolve to a real location in a real document — a page, a heading, a line, a cell.

End-to-end encrypted memory for AI agents — portable, yours forever.

Code search that lets AI coding agents find the right files in fewer steps. Use the hosted endpoint or self-host, works with Claude Code, Copilot and Cursor via MCP.

Agentic terminal AI assistant with a Bubble Tea TUI, code-graph review, semantic search, multi-provider LLMs, and MCP tools.

Claude code memory, or maybe not code.

Local-first trust layer for AI coding agents: structural prompt-injection and action guards, secret scanning, semantic memory, code review, and 17 MCP tools. No model API required.

Production-ready .NET 10 RAG library with hybrid vector + keyword search, multi-backend storage (SQLite, PostgreSQL, Neo4j, Qdrant), and MCP server integration.