Penfield Memory

AI 与智能体

by penfieldlabs

为 AI agents 提供持久化 memory 与 knowledge graph,支持 hybrid search、上下文检查点等。

什么是 Penfield Memory

为 AI agents 提供持久化 memory 与 knowledge graph,支持 hybrid search、上下文检查点等。

README

Penfield

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.


Quick Start

Claude (Desktop, Mobile, Web)

Add as a custom connector in Settings → Connectors:

code
Name: Penfield
Remote MCP server URL: https://mcp.penfield.app

Claude Code

bash
claude mcp add --transport http --scope user penfield https://mcp.penfield.app

Cursor

One-click install:

Install Penfield in Cursor

Cut and paste into your browser:

code
cursor://anysphere.cursor-deeplink/mcp/install?name=Penfield&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIm1jcC1yZW1vdGUiLCJodHRwczovL21jcC5wZW5maWVsZC5hcHAvIl19

Or add manually to ~/.cursor/mcp.json:

json
{
  "mcpServers": {
    "Penfield": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.penfield.app/"]
    }
  }
}

Windsurf, Cline, Roo Code, and Others

Add to your MCP configuration file:

json
{
  "mcpServers": {
    "Penfield": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.penfield.app/"]
    }
  }
}
AppConfig Location
Windsurf~/.codeium/windsurf/mcp_config.json
ClineVS Code Settings → Cline → MCP Servers
Roo CodeVS Code Settings → Roo Code → MCP Servers
Zed~/.config/zed/settings.json under "context_servers"

Gemini CLI

bash
gemini mcp add penfield -- npx -y mcp-remote https://mcp.penfield.app/

Or add to ~/.gemini/settings.json:

json
{
  "mcpServers": {
    "Penfield": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.penfield.app/"]
    }
  }
}

What You Get

17 tools for persistent memory:

CategoryTools
Memorystore, recall, search, fetch, update_memory
Knowledge Graphconnect, disconnect, explore
Contextawaken, reflect, save_context, restore_context, list_contexts
Artifactssave_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.


How It Works

  1. Sign up at portal.penfield.app/sign-up
  2. Connect using one of the methods above
  3. Authenticate when prompted (OAuth flow)
  4. Start using — your agent now has persistent memory

Every session should start with:

code
awaken()     # Load identity and personality context
reflect()    # Orient on recent work (default: last 7 days)

Without these, your agent starts cold with no context.


Documentation


Use Cases

Personal assistant that remembers

  • Your preferences compound over time
  • Picks up conversations where you left off
  • Learns how you like things done

Development workflows

  • Track investigation threads across sessions
  • Remember architectural decisions and why they were made
  • Hand off context between coding sessions

Research and writing

  • Build knowledge graphs of connected ideas
  • Store insights and corrections as understanding evolves
  • Checkpoint progress on long-running projects

Also Available

OpenClaw Native Plugin — If you use OpenClaw, the native plugin is 4-5x faster (no MCP proxy layer):

bash
openclaw plugins install openclaw-penfield
openclaw penfield login

openclaw-penfield on GitHub · openclaw-penfield on npm

API — Direct HTTP access at api.penfield.app for custom integrations.


Links

penfield-mcp MCP server


Copyright © 2025 Penfield™. All rights reserved.

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Penfield Memory 是什么?

为 AI agents 提供持久化 memory 与 knowledge graph,支持 hybrid search、上下文检查点等。

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