The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Penfield MCP listing page.
Persistent memory for AI agents. Store decisions, preferences, and context that survive across sessions. Build knowledge graphs that compound over time. Works with Claude, Cursor, Windsurf, Gemini CLI, and any MCP-compatible tool.
Add as a custom connector in Settings → Connectors:
One-click install:
Cut and paste into your browser:
Or add manually to ~/.cursor/mcp.json:
Add to your MCP configuration file:
| App | Config Location |
|---|---|
| Windsurf | ~/.codeium/windsurf/mcp_config.json |
| Cline | VS Code Settings → Cline → MCP Servers |
| Roo Code | VS Code Settings → Roo Code → MCP Servers |
| Zed | ~/.config/zed/settings.json under "context_servers" |
Or add to ~/.gemini/settings.json:
17 tools for persistent memory:
| Category | Tools |
|---|---|
| Memory | store, recall, search, fetch, update_memory |
| Knowledge Graph | connect, disconnect, explore |
| Context | awaken, reflect, save_context, restore_context, list_contexts |
| Artifacts | save_artifact, retrieve_artifact, list_artifacts, delete_artifact |
Hybrid search combining BM25 (keyword), vector (semantic), and graph (connections) for recall that actually finds what you need.
Cross-platform sync — same memory, same knowledge graph, regardless of which tool you connect from.
Every session should start with:
Without these, your agent starts cold with no context.
Personal assistant that remembers
Development workflows
Research and writing
OpenClaw Native Plugin — If you use OpenClaw, the native plugin is 4-5x faster (no MCP proxy layer):
openclaw-penfield on GitHub · openclaw-penfield on npm
API — Direct HTTP access at api.penfield.app for custom integrations.
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