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MCP server · RAG

ChatCrystal

Crystallize knowledge from AI conversations. Import from Claude Code / Cursor / Codex CLI, summarize with LLM, search by semantics.

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Scored 6 months ago · breakdown

About ChatCrystal

ChatCrystal is an MCP server in the RAG category: crystallize knowledge from AI conversations. Import from Claude Code / Cursor / Codex CLI, summarize with LLM, search by semantics.

Install

From source
git clone https://github.com/ZengLiangYi/ChatCrystal

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

ChatCrystal

Turn your AI conversations into searchable knowledge

GitHub release npm Node.js Platform Website

English | 简体中文


ChatCrystal collects conversations from AI coding tools, distills them into structured notes with LLMs, and builds a local searchable knowledge base from your real problem-solving history.

Supported sources: Claude Code, Cursor, Codex CLI, Trae, and GitHub Copilot.

Quick Start

Desktop App (Recommended)

Download the latest Windows installer from GitHub Releases. After installing, launch ChatCrystal, configure your LLM and embedding providers in Settings, then click Import.

CLI / Web

npm install -g chatcrystal
crystal serve -d
crystal import

Then open http://localhost:3721 in your browser.

What It Does

  • Imports AI coding conversations from local tool data directories.
  • Distills conversations into structured notes with titles, summaries, conclusions, snippets, and tags.
  • Searches knowledge semantically with embeddings and relation-aware result expansion.
  • Builds a knowledge graph across related notes and decisions.
  • Exposes CLI and MCP tools so agents can recall and write back reusable experience.
  • Runs locally with configurable LLM and embedding providers.

Screenshots

Common Commands

crystal status                          # Server status and DB stats
crystal import [--source claude-code]   # Scan and import conversations
crystal search "query" [--limit 10]     # Semantic search
crystal notes list [--tag X]            # Browse notes
crystal notes get <id>                  # View note detail
crystal summarize --all                 # Batch summarize
crystal config get                      # View config
crystal serve -d                        # Start server in background
crystal serve stop                      # Stop background server
crystal mcp                             # Start MCP stdio server

Documentation

Topic English 简体中文
User guide docs/USER_GUIDE.md docs/USER_GUIDE.zh-CN.md
Development docs/DEVELOPMENT.md docs/DEVELOPMENT.zh-CN.md
MCP and agents docs/MCP.md docs/MCP.zh-CN.md
Experience quality gate docs/EXPERIENCE_GATE.md docs/EXPERIENCE_GATE.zh-CN.md
Agent skills docs/agent-skills.md docs/agent-skills.zh-CN.md

Requirements

  • Node.js >= 20
  • An LLM provider for summarization
  • An embedding provider for semantic search

LLM and embedding providers are configured separately. Large language models such as Claude, GPT, and Qwen are not embedding models. See the user guide for provider examples.

Local Development

git clone https://github.com/ZengLiangYi/ChatCrystal.git
cd ChatCrystal
npm install
npm run dev

Development server ports:

  • API/server: http://localhost:3721
  • Vite client: http://localhost:13721

See docs/DEVELOPMENT.md for architecture, testing, build, and release details.

License

MIT

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About ChatCrystal

How do I install ChatCrystal?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is ChatCrystal safe to use with an AI agent?

Its trust score is 39 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is ChatCrystal still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.