What is ChatCrystal?
ChatCrystal collects conversations from AI coding tools (Claude Code, Cursor, Codex CLI, Trae, GitHub Copilot), distills them into structured notes using LLMs, and builds a local searchable knowledge base from your real problem-solving history. It is for developers who want to turn AI-assisted coding conversations into reusable knowledge.
How to use ChatCrystal?
Install the Windows desktop app from GitHub Releases, or run npm install -g chatcrystal and use crystal serve -d plus crystal import to start a CLI/Web server at http://localhost:3721. For a Docker cloud deployment, clone the repo and run docker compose up -d. Configure an LLM provider and an embedding provider in Settings, then import conversations from supported tools.
Key features of ChatCrystal
- Imports AI coding conversations from local tool data directories.
- Distills conversations into structured notes with titles, summaries, and tags.
- Searches knowledge semantically with embeddings and relation-aware results.
- Builds a knowledge graph across related notes and decisions.
- Exposes both CLI and MCP tools for agent recall and write-back.
- Runs locally with configurable LLM and embedding providers.
Use cases of ChatCrystal
- Turning Claude Code or Cursor chat logs into a searchable personal knowledge base.
- Reusing past solutions by semantically searching for similar problems.
- Building a knowledge graph to visualize relationships between coding decisions.
- Using MCP tools to let AI agents recall and contribute to experience notes.
- Synchronizing conversation history from multiple devices to a self-hosted cloud instance.
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