ppl
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@pplGive me my daily briefing and suggest who I should reach out to today."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ppl
Relational memory for you and your AI.
ppl is a personal CRM for you and the AI assistants you choose. Keep contacts, conversation notes, birthdays and follow-ups together. Work in the browser or authorize an assistant to use the same records.
Read about ppl, choosing a personal CRM, or importing your contacts.
The guides and free tools cover client setup, product comparisons and contact migration. Start with your client’s Claude, ChatGPT, Cursor, or VS Code guide. Before importing, the local CSV checker can flag common file issues without uploading your contacts. Writers and directory maintainers can use the press kit for current product facts, the original logo and public screenshots.
Developer home: ppl-crm.github.io. Try the fictional relationship-memory demo without connecting an account.
Connect your AI
Hosted MCP server: https://withppl.com/mcp
The hosted service is available now. A self-hosted version is coming soon. Your agent connects over Streamable HTTP with a Bearer token.
Start with your client
Use the connection guide for client setup or the developer guide for authentication, permissions, starter recipes and recovery. New users can create an account during connection and verify email ownership. Some clients require a separate configuration step; available features can depend on account plans and administrator settings.
Agent connection flow
POST https://withppl.com/api/agent/connect/requestwith{"client_name": "Your agent"}Show the human the
approve_url. They sign in or create an account, verify email ownership and review the requested permissions.Poll the returned
poll_urlconservatively until approved and save the one-timeapi_tokenin a protected credential store. Stop on denial or expiration.Use the token with the MCP server or REST API.
MCP clients that support OAuth (Claude, ChatGPT, and others) can connect with standard OAuth 2.0: dynamic client registration, PKCE, and refresh tokens. See docs/oauth.md.
Machine-readable: ppl.json, llms.txt, and the OpenAPI spec for the REST API.
Related MCP server: MIND MCP Server
MCP registry
Registered as io.github.ppl-crm/ppl in the official MCP registry. See server.json.
Examples
Python briefing examples - a dependency-free REST client and an MCP SDK client
Node MCP client - connect with the MCP TypeScript SDK
ppl-memory PyPI package - LangGraph, CrewAI, and AutoGen adapters
Docs
Agent integration guide - task-scoped workflows, tools, and patterns
OAuth for MCP clients - Dynamic Client Registration flow
License
MIT. See LICENSE.
This server cannot be deployed
Maintenance
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