🧠 The Brain for Your AI — Local-first memory engine for AI agents. Store, recall, and search memories with semantic embeddings. Single Rust binary, zero config, fully offline.

Convert AI coding agent sessions (Claude Code, Cursor, Codex, Gemini, OpenCode, Kimi Code, Hermes) into self-contained, embeddable HTML replays

PC Engine / TurboGrafx-16 / SuperGrafx / PCE CD-ROM² emulator, debugger, and embedded MCP server for macOS, Windows, Linux, BSD and RetroArch.

Git-native persistent memory for AI coding agents. Implements Google OKF v0.2 with sub-300µs in-memory BM25 search, embedded MCP server, and progressive disclosure. Slashes token bloat by 80% with zero external databases or dependencies. Built in pure Go.

Tool-to-Agent Protocol: tools can be smart without embedded LLM calls.

A super light-weight embedded code search engine CLI (AST based) that just works - improves speed and efficiency for coding agent 🌟 Star if you like it!

One memory shared by Claude Code, Codex, Cursor, Copilot CLI, OpenClaw and 20 more coding agents, built from the session history already on disk. A fix found in one agent comes back in any of them, including months of sessions from before you installed it. No LLM, no embeddings, one local Go binary.

Official Jina AI Remote MCP Server

A semantic search engine for files and code.

Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.

Persistent memory for Claude Code. Your AI never starts from scratch again.

Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read

Semantic Search & Call Graphs for AI Agents (100% Local)

Universal memory runtime for AI agents

AI-powered spec generation and review using multi-repo code graph intelligence for backend teams that ship to production.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Semantic codebase indexing and search for OpenCode, Claude, Codex, Pi, Jcode, and MCP hosts. Powered by Rust and tree-sitter.

Your coding agent starts every session blank. Rekal is the memory your team is missing

Persistent memory graph for AI agents. Facts, decisions, entities, and relationships that survive across sessions, tools, and providers. MCP server — works with Claude, Cursor, ChatGPT, and any MCP client.

Code search MCP for Claude Code. Make entire codebase the context for any coding agent.

Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python, TypeScript, Rust, Go, .NET, Java

MCP-native code retrieval for AI agents — 84-88% fewer read tokens, BM25F + semantic search, AST chunks, session dedup

Multi-repo semantic code search MCP server in Rust — hybrid vector + BM25 retrieval, tree-sitter AST chunking, fully offline. For OpenCode, Claude Code, Cursor, and any MCP client.

Vestige enhances agents by deterministic root-cause retrieval that reaches backward through time to find the quiet change, decision, or service that caused today’s failure, not the lookalike.