origin-mcp

MCP connector for Origin.

Origin runs quietly behind the AI tools you already use. It gives your AI a place to carry decisions, lessons, gotchas, and project context instead of rediscovering them in every new chat.

origin-mcp lets Claude Code, Cursor, Codex, Claude Desktop, Windsurf, Gemini CLI, and other MCP clients read and write to your local Origin runtime through the Model Context Protocol. The daemon owns storage, search, embeddings, and background refinement. This repo is only the MCP connector.

Install

Add to your MCP config (Claude Code, Cursor, Claude Desktop, Windsurf, Gemini CLI):

{
  "mcpServers": {
    "origin": {
      "command": "npx",
      "args": ["-y", "origin-mcp"]
    }
  }
}

Or install the binary directly:

# Via Homebrew
brew install 7xuanlu/tap/origin-mcp

# Via cargo
cargo install origin-mcp

Then add the binary path to your MCP config:

{
  "mcpServers": {
    "origin": {
      "command": "origin-mcp"
    }
  }
}

How it works

origin-mcp connects to the Origin daemon running on 127.0.0.1:7878.

Claude Code / Cursor / Claude Desktop
    |
    | MCP (stdio)
    v
origin-mcp
    |
    | HTTP
    v
Origin runtime
    |
    v
Local SQLite + embeddings + knowledge graph

If the daemon is not running, origin-mcp returns an actionable setup message. Install the Origin desktop app, or install the headless runtime:

curl -fsSL https://raw.githubusercontent.com/7xuanlu/origin/main/install.sh | bash
export PATH="$HOME/.origin/bin:$PATH"
origin setup
origin install
origin status

Setup has three paths:

• Basic Memory: store, search, and recall immediately. No model download or API key.
• On-device Model: private local extraction and background refinement after model download.
• Anthropic Key: richer extraction and background refinement using your API key.

Memory tools

Diagnostic tool

doctor matches the origin doctor CLI command. It is not part of the memory loop. It exists so an MCP client can explain setup and refinement problems without guessing.

What agents should know

The server ships with proactive-capture instructions that guide agents to store the right things at the right granularity. Key ideas:

• Two mental models: profile (about the user) vs knowledge (about the world). Agents should think in these terms when deciding what to store.
• One idea per memory. "Prefers TDD" and "uses pytest" are two memories, not one. Specific memories retrieve better than broad summaries.
• Include the why. "Switched to dark mode because of migraines" is more useful than "uses dark mode."
• Omit memory_type. Let the backend auto-classify. Agents get it wrong more often than the classifier.
• Anti-noise rules. Don't store conversation filler, tool output, or things trivially re-derivable from code.

See src/tools.rs for the full with_instructions text that agents receive.

Options

--origin-url <URL>    Override Origin server URL (default: http://127.0.0.1:7878)

What Origin does with your memories

Origin works in Basic Memory mode without an on-device model or API key: storage, search, recall, and MCP memory are available immediately.

When the user opts into an on-device model or Anthropic key, Origin can refine memories over time:

• Deduplication. Overlapping memories are merged automatically.
• Page distillation. Related memories are clustered into pages: compact, wiki-style summaries that save tokens on retrieval.
• Knowledge graph. Entities and relations are extracted and linked, so "Alice leads the deploy refactor" connects Alice, the project, and the decision.
• Contradiction detection. When new information conflicts with existing memories, Origin surfaces it for your review.

The longer you use it, the better the retrieval gets.

Requirements

• Origin runtime running locally (via the desktop app or origin setup / origin install)
• macOS Apple Silicon (M1+) at v0.1.0. Linux x64 binaries are built but not yet tested in production.

License

MIT

Links

• Origin: the desktop app, daemon, and core engine
• Model Context Protocol: the protocol spec