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Penfield Memory

Registre officiel Recherche et web

Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.

Code source Site web Documentation

Que pouvez-vous faire avec Penfield Memory ?

  • Your preferences compound over time
  • Picks up conversations where you left off
  • Learns how you like things done
  • Track investigation threads across sessions
  • Remember architectural decisions and why they were made
  • Hand off context between coding sessions
  • Build knowledge graphs of connected ideas
  • Store insights and corrections as understanding evolves

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

Remote (streamable-http)
Claude Code 
claude mcp add --transport http penfield-memory 'https://mcp.penfield.app/'
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "penfield-memory": {
            "type": "http",
            "url": "https://mcp.penfield.app/"
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Penfield
  2. Quick Start
  3. What You Get
  4. How It Works
  5. Documentation
  6. Use Cases
  7. Also Available
  8. Links

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:

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

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

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

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

Or add to ~/.gemini/settings.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:

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):

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.

Copyright © 2025 Penfield™. All rights reserved.

Questions fréquentes

Qu'est-ce que Penfield Memory ?

Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.

Comment installer Penfield Memory ?

Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http penfield-memory 'https://mcp.penfield.app/'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Penfield Memory ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

Penfield Memory est-il open source ?

Oui. Son code est sur GitHub sous licence AGPL-3.0.

Qui maintient Penfield Memory ?

Il est publié par penfieldlabs. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.