Model Context Protocol (MCP) Settings
Access server URLs and documentation for integrating Pieces Long-Term Memory with Cursor, GitHub Copilot, and other tools that support the Model Context Protocol. The MCP server enables connectivity between Large Language Models (LLMs) and your personal context stored by the Long-Term Memory Engine (LTM-2.7).
To access MCP settings, click your User Profile in the top left, then hover over Settings and select MCP.
Model Context Protocol (MCP) settings showing server URLs and View Documentation option
Available Servers
Copy the server URLs to configure MCP integrations in compatible IDEs and code editors. Multiple server URLs are available, including the latest schema version and previous versions for compatibility.
Understanding Server URLs
The MCP settings display server URLs that your development tools or AI applications, such as Cursor or GitHub Copilot, will use to communicate directly with your local PiecesOS MCP server.
Copying Server URLs
View Documentation
Access detailed guides that explain how to leverage MCP integrations with popular development environments, such as Cursor and GitHub Copilot.
Opening MCP Documentation
The documentation provides comprehensive guides on:
- Setting Up Integrations: Step-by-step instructions for configuring MCP in Cursor, GitHub Copilot, and other tools
- Use Cases: Examples of how MCP enhances your coding and debugging experiences
- Troubleshooting: Solutions for common integration issues and configuration problems
Example Use Cases
MCP enhances your coding and debugging experiences in several ways:
- Context-Rich Debugging: Instantly retrieve logs, historical debugging notes, or team discussions directly from PiecesOS when troubleshooting within Cursor
- Contextual Queries: Access historical code implementations, error resolutions, or previously encountered bugs within GitHub Copilot for quicker coding solutions
For more use cases and detailed setup instructions, refer to the MCP documentation.
MCP Connections
Connect Pieces to supported MCP clients with one click. Pieces writes to each client's global or user-level MCP config and, when supported, also creates the matching global rule or skill file automatically.
MCP Connections section showing supported clients with one-click Connect buttons
The MCP Connections section shows your connection status (e.g., "Connected 4 of 6") and a Refresh Connections button to update the status.
Supported Clients
| Client | Description |
|---|---|
| Claude Desktop | Connect Pieces to Claude Desktop for memory-backed conversations |
| Cursor | Connect Pieces to Cursor so your IDE has access to long-term memory |
| GitHub Copilot | Connect Pieces to GitHub Copilot for context-aware code suggestions |
| Codex | Connect Pieces to Codex so both the CLI and IDE extension can connect to your memory via MCP |
| Google Gemini CLI | Connect Pieces to Google Gemini CLI so terminal-based workflows can use MCP-backed context |
| Antigravity | Connect Pieces to Antigravity so its agent panel can access your long-term memory over MCP |
| Claude Code | Connect Pieces to Claude Code so terminal-based workflows can use long-term memory context |
| OpenClaw | OpenClaw setup is documented separately for now. Click View Docs to open the setup guide |
Connecting a Client
Managing Connected Clients
Once connected, a green checkmark appears next to the client name. To disconnect or reconfigure:
Next Steps
Now that you understand how to access MCP server URLs and documentation, learn how to set up MCP with Cursor or integrate with GitHub Copilot to start using Pieces Long-Term Memory in your development workflow.