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Cursor Memory MCP

Cursor Memory MCP

Local
github.com/zjmwqxMemory & Knowledge1Updated 72w ago

About Cursor Memory MCP

Cursor Memory MCP is a server for AI assistants that records project task context as formatted `.mdc` files in Cursor's rules directory. It helps preserve work history for later reference and supports Chinese and international content.

Key features

  1. 01Create task memory files
  2. 02Format files for Cursor rules
  3. 03Preserve task execution context
  4. 04Support Chinese and international content
  5. 05Work on Windows, macOS, and Linux

Use cases

  1. 01Record coding task outcomes in a project
  2. 02Refer back to earlier task context
  3. 03Create Cursor rule files from task summaries

MCP support

Exposes a create_cursor_memory tool through MCP, allowing AI assistants to create `.mdc` files in a project's `.cursor/rules/` directory.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Cursor Memory MCP

Python Version License: MIT smithery badge

🧠 Enable AI assistants to create and manage project memory files in Cursor through a simple MCP interface.

The Cursor Memory MCP Server provides a bridge between AI assistants and Cursor's project memory system through the Model Context Protocol (MCP). It allows AI models to automatically create and manage .mdc memory files in your project's .cursor/rules/ directory.

Project Screenshot Project Screenshot

✨ Core Features

  • 🧠 memory record: Automatically create task memory files in .cursor/rules/ directory
  • 📝 structure format: Generate properly formatted .mdc files following Cursor specifications
  • 🔄 context saving: Preserve task execution context for future reference
  • 🌐 multi-language: Full support for Chinese and international content
  • 💻 cross-platform: Works seamlessly on Windows, macOS, and Linux
  • ⚡ MCP standard protocol: Built on the Model Context Protocol for seamless AI integration

🚀 Quick Start

Installing via Smithery

To install Cursor Memory MCP for Cursor's MCP client automatically via Smithery:

npx -y @smithery/cli install cursor-memory-mcp --client cursor
Installing via pip

Install using uv for better performance and isolation:

# Install globally as a tool
uv tool install cursor-memory-mcp

# Update PATH to use the tool
uv tool update-shell

step1 . cursor settings --> MCP --> add configuration (reffered later)

step2 . cursor settings --> RULES --> add user rule:

After task execution is completed, use `cursor memory` to track task execution records

step3 . call agent to help you with coding

when you dev step by step, proj rules will record cursor operation history, and when cursor need them, it will reffer it and do your job with memory.

Installing for Development

For development and contributing:

# Clone and set up development environment
git clone https://github.com/yourusername/cursor-memory-mcp.git
cd cursor-memory-mcp

# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate  # Linux/macOS
# or
.venv\Scripts\activate     # Windows

# Install with development dependencies
pip install -e ".[dev]"
Alternative: Using uv (Recommended)
# Install globally
uv tool install cursor-memory-mcp

# For development
git clone https://github.com/yourusername/cursor-memory-mcp.git
cd cursor-memory-mcp
uv venv
source .venv/bin/activate  # Linux/macOS
# or
.venv\Scripts\activate     # Windows
uv pip install -e ".[dev]"

🔌 MCP Integration

Cursor Integration

Add this configuration to your Cursor MCP settings:

{
    "mcpServers": {
        "cursor-memory-mcp": {
            "command": "uv",
            "args": [
                "tool",
                "run",
                "cursor-memory-mcp",
            ]
        }
    }
}
Development Configuration

For development with local installation:

{
    "mcpServers": {
        "cursor-memory-mcp": {
            "command": "uv",
            "args": [
                "--directory",
                "path/to/cloned/cursor-memory-mcp",
                "run",
                "cursor-memory-mcp",
            ]
        }
    }
}

💡 Available Tools

The server provides one powerful tool for memory management:

Memory Creation Tool

Create project memory files with comprehensive context:

result = await call_tool("create_cursor_memory", {
    "task_summary": "实现了用户认证系统,包括JWT token生成、密码加密验证和权限管理功能",
    "task_name": "user_authentication_system",
    "task_description": "用户认证和授权系统实现"
})

Parameters:

ParameterTypeRequiredDescription
task_summarystring✅详细的任务执行上下文总结
task_namestring✅简短的任务名称(用作文件名)
task_descriptionstring⚪可选的详细任务描述
project_pathstring✅当前项目的绝对路径

Validation Rules:

  • task_name must contain only letters, numbers, underscores, and hyphens
  • task_summary cannot be empty or whitespace only
  • Files are automatically timestamped if duplicates exist

📁 Generated File Format

The server creates .mdc files with the following structure:

---
description: "get the summary of previous step: {task_description}"
globs:
alwaysApply: false
---
{task_summary}

🤝 Contributing

We welcome contributions of all kinds! Please see our Contributing Guide for details.

🙏 Acknowledgments


Made with ❤️ for the AI development community

Star ⭐ this repo if you find it helpful!

Comments

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