Penfield Memory
Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.
ماذا يمكنك أن تفعل مع 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
التثبيت
أضف هذا إلى إعدادات MCP في عميلك (Claude Desktop: claude_desktop_config.json، وCursor: .cursor/mcp.json، ويستخدم VS Code وغيره الصيغة نفسها «mcpServers»).
claude mcp add --transport http penfield-memory 'https://mcp.penfield.app/'
{
"mcpServers": {
"penfield-memory": {
"type": "http",
"url": "https://mcp.penfield.app/"
}
}
}
التوثيق
مأخوذ من ملف README للمشروع على GitHub ويُحدَّث أسبوعيًا. تفتح الروابط على GitHub.
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/"]
}
}
}
| 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" |
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:
| 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.
How It Works
- Sign up at portal.penfield.app/sign-up
- Connect using one of the methods above
- Authenticate when prompted (OAuth flow)
- 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
- Tools Reference — All 17 tools with parameters and examples
- Memory Types — The 11 memory types and when to use each
- Relationships — The 24 relationship types for connecting memories
- AI Agent Guide — Instructions for AI agents using Penfield
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.
Links
- MCP: mcp.penfield.app
- Website: penfield.app
- Portal: portal.penfield.app
- Cursor Directory: cursor.directory/mcp/penfield
- X: @penfieldlabs
- GitHub: @penfieldlabs
Copyright © 2025 Penfield™. All rights reserved.
الأسئلة الشائعة
ما هو Penfield Memory؟
Persistent memory and knowledge graphs for AI agents. Hybrid search, context checkpoints, and more.
كيف أثبّت Penfield Memory؟
يعمل كخادم بعيد. في Claude Code: claude mcp add --transport http penfield-memory 'https://mcp.penfield.app/'. وفي العملاء الآخرين، الصق إعداد JSON من هذه الصفحة في إعدادات MCP الخاصة بهم.
هل يحتاج Penfield Memory إلى مفتاح API؟
لا يذكر إدراجه في السجل أي مفتاح أو سر إلزامي. قد تتطلب بعض الميزات حسابًا لدى الخدمة التي يتصل بها.
هل Penfield Memory مفتوح المصدر؟
نعم. شيفرته متاحة على GitHub بترخيص AGPL-3.0.
من يصون Penfield Memory؟
ينشره penfieldlabs. يدرجه AI.tn لكنه لا يصونه ولا يوصي به.
من سجل MCP الرسمي. الإدراج ليس توصية: راجع شيفرة الخادم وصلاحياته قبل منحه الوصول إلى بياناتك.