ChatCrystal

ChatCrystal

Local-first AI PKM for coding conversations

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ChatCrystal is a local-first AI PKM app for developers who solve real problems with Claude Code, Cursor, Codex CLI, Trae, and GitHub Copilot.

It turns scattered AI coding conversations into structured notes, semantic search, a tag knowledge graph, Markdown exports, and MCP memory your agents can reuse. If this fits your workflow, a star helps more builders find a private, local-first way to keep their AI work memory.

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.

Docker Cloud

Prefer self-hosting ChatCrystal for multiple devices? See Docker Cloud Deployment after the product overview.

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 tag knowledge graph where knowledge points are tags and edges show normalized co-occurrence.
• 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

Requirements

• Node.js >= 24
• 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.

ChatCrystal includes first-class OrcaRouter support for LLM generation. OrcaRouter is OpenAI-compatible; its Base URL is built in, so enter only your API Key and use Settings to fetch and select an available model.

Local Development

git clone https://github.com/ZengLiangYi/ChatCrystal.git
cd ChatCrystal
corepack enable
pnpm install
pnpm 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.

Docker Cloud Deployment

The default Compose deployment runs only the ChatCrystal service. It stores data in the chatcrystal-data volume mounted at /data inside the container.

git clone https://github.com/ZengLiangYi/ChatCrystal.git
cd ChatCrystal
docker compose up -d

The default docker-compose.yml pulls ghcr.io/zengliangyi/chatcrystal:latest from GitHub Container Registry. Set CHATCRYSTAL_IMAGE_TAG to pin a published version. To build from source instead, run docker compose -f docker-compose.yml -f docker-compose.build.yml up -d --build.

To update an existing Docker deployment, run docker compose pull && docker compose up -d. Maintainers only: after the first GHCR publish, make the ghcr.io/zengliangyi/chatcrystal package public in GitHub Packages; the release workflow verifies anonymous pull access before passing.

Compose binds ChatCrystal to 0.0.0.0:3721 by default so other devices can reach the cloud core through the host IP. Set CHATCRYSTAL_HOST_PORT to change the host port, or set BIND_ADDRESS=127.0.0.1 when a local-only reverse proxy fronts it. For public cloud access, an HTTPS reverse proxy is recommended for safer token transport.

On Windows Docker Desktop, a published port may still need extra host networking configuration before it is reachable through the host LAN IP. For cloud-mode testing, verify http://<host-ip>:<host-port>/api/health from the client device first; if it cannot connect, configure Windows port forwarding/firewall rules or deploy the cloud core on a real remote host.

On first start without CHATCRYSTAL_API_TOKEN, open the Web UI and enter the setup code printed in container logs or stored at /data/setup-code, then choose one shared API token for your devices.

To rotate or reset the Docker cloud token:

# If you still know the current token, rotate it online.
crystal --base-url https://chatcrystal.example.com token rotate "new-long-token-at-least-16-chars" --current "old-token"
crystal connect https://chatcrystal.example.com --token "new-long-token-at-least-16-chars"

# If you forgot the token and did not set CHATCRYSTAL_API_TOKEN, reset stored auth in the container.
docker compose exec chatcrystal crystal token reset --yes
docker compose logs chatcrystal --tail=80
docker compose exec chatcrystal cat /data/setup-code

If your deployment sets CHATCRYSTAL_API_TOKEN, that environment variable is the active token source. Change it in your .env or Compose environment and recreate the container with docker compose up -d --force-recreate.

To use an existing Ollama or external API, configure provider URLs in the Web UI or environment. In Docker, localhost means inside the container; use CHATCRYSTAL_DOCKER_LLM_BASE_URL and CHATCRYSTAL_DOCKER_EMBEDDING_BASE_URL for Compose-time provider URL overrides. Docker Desktop can reach host Ollama at http://host.docker.internal:11434, or you can use a remote HTTPS/OpenAI-compatible API.

Import from a Device into the Cloud Instance

Install or run the CLI on the device that has Claude Code, Cursor, Codex CLI, Trae, or GitHub Copilot history:

crystal connect https://chatcrystal.example.com --token "your-long-token"
crystal import --yes

The CLI scans local histories, parses them locally, and uploads normalized conversations to the cloud. The cloud never scans your local filesystem. Imported conversations are not summarized automatically; use the Web UI or crystal summarize --all when you are ready. HTTPS is recommended for cloud access, but HTTP works when that is the deployment you choose.

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License

Apache License 2.0