Your AI connector for Cursor
Cursor AI is one of the most used tools right now when it comes to coding, both for people with technical and non-technical backgrounds, but even the best AI agents are limited without memory.
Enter Pieces: your free AI connector for Cursor, enabling real-time access to your personal workflow history, project knowledge, and saved snippets. Using our Model Context Protocol (MCP), Pieces integrates directly with Cursor to bring project-aware, long-term memory into the chat sidebar, no digging through commits, comments, or past threads.
Whether you’re running Cursor on macOS, Windows 10, or Windows 11, this integration turns Cursor AI into a true coding copilot with context.
Why use Pieces as your AI connector for Cursor?
Pieces makes Cursor more than a smart autocomplete tool; it makes it a full-fledged memory assistant.
Add long-term context to your AI chat
When you connect Pieces MCP to Cursor, you unlock something most IDEs can’t offer: an AI agent that remembers.
Ask about past work: “Did I fix this bug before?” or “What was my prompt from last Tuesday?”
Access reusable knowledge: Get working snippets, prompt chains, and debug traces on demand.
Avoid repeating yourself: The AI pulls answers from your actual project history, not just the current file, and creates an interactive workstream.
Works natively on macOS, Windows 10, and Windows 11
The Pieces MCP + Cursor runs on top of PiecesOS, which is cross-platform and built for developers who need full local control with zero vendor lock-in.
Compatible with both Intel and ARM Macs
Supports current Windows 10 and 11 builds
Works alongside other tools like VS Code, Raycast, JetBrains, and many others.
Set up your free AI connector for Cursor
Step 1: Install and run PiecesOS
PiecesOS is the engine that captures, stores, and streams your workflow context to Cursor via MCP.
Download for macOS or Windows
Grant screen/audio permissions when prompted (macOS only)
Enable Long-Term Memory (LTM-2.5) in the PiecesOS Quick Menu
Pieces works fully offline by default. Nothing is sent to external servers unless you opt in to Personal Cloud or third-party models.
Step 2: Find your MCP endpoint
To integrate with Cursor, you’ll need your local SSE endpoint:
Open the PiecesOS Quick Menu or the Pieces Desktop App
Copy the endpoint under Model Context Protocol (MCP)
Example:
http://localhost:39300/model_context_protocol/2024-11-05/sse
Step 3: Connect MCP in Cursor
Open Cursor > Settings > MCP
Add a new global MCP server
Paste your endpoint in this format:
Save the file and refresh the MCP settings
Ensure a green status indicator confirms the server is active
How to use Cursor AI with Pieces
Once configured, using the MCP integration is seamless:
Open the chat panel (⌘+i / Ctrl+i)
Switch to Cursor Agent Mode
Prompt as usual, then click Use Tool when the ask_pieces_ltm tool is suggested
Try questions like:
“What was I doing yesterday on this file?”
“Show me similar errors I fixed recently”
“Summarize recent refactors from my snippets”
Pieces will retrieve context from your local memory and serve it right in the Cursor chat window.
Customize your Cursor AI experience
Pieces works with Cursor’s existing customization features:
Add User Rules in Settings > Rules to tailor LTM responses
Adjust model behavior for tools like Claude, GPT-4, or Gemini
Disable auto-select and manually pick agents if needed
Tip: You can also use this with Cursor AI alternatives or custom LLM backends via the MCP endpoint.
Why do developers use Pieces as their Cursor AI connector
Works across macOS and Windows
Free and local-first with optional cloud sync
Adds long-term memory to your Cursor chat
Makes prompts, snippets, and decisions reusable
Extends Cursor AI beyond just the current file or tab
Open source tooling and GitHub support for advanced workflows
Try Pieces with Cursor today
Whether you're just learning how to use Cursor AI or looking for a smarter alternative with long-term memory, Pieces adds the missing layer of context and speed.
Try it for free today!