cursor-history-mcp
MCP server for browsing, searching, exporting, and backing up your Cursor AI chat history directly into Claude via natural language.
README
Cursor History MCP
🇨🇳 中文文档 | 🇫🇷 Français | 🇪🇸 Español
<p align="center"> <img src="docs/cursor-history-mcp-logo.jpg" alt="cursor-history-mcp logo" width="200"> </p>
MCP server for browsing, searching, exporting, and backing up your Cursor AI chat history.
Bring your Cursor AI chat history directly into Claude. Search past conversations, export sessions, create backups, and generate year-in-review reports—all through natural language. Built on the Model Context Protocol for seamless AI assistant integration.
Free, open-source, and MIT licensed. Built by the community, for the community.
Why This Project?
There are other Cursor history tools out there (like the Python-based Cursor-history-MCP). Here's what makes this one different:
| Feature | cursor-history-mcp (this project) | Other Solutions |
|---|---|---|
| 📦 Setup | ✅ npx cursor-history-mcp - zero install |
❌ Docker, Python, dependencies |
| ⚡ Speed | ✅ Instant - direct SQLite reads | ❌ Slow - requires LLM vectorization |
| 🔍 Search | ✅ Grep-style text matching - precise & stable | ❌ Vector retrieval - unpredictable results |
| 🤖 LLM Required | ✅ No - works offline | ❌ Yes - needs Ollama/embeddings |
| 🛠️ Language | ✅ TypeScript (type-safe) | ⚠️ Python |
| 💾 Backup/Restore | ✅ Built-in | ❌ Not available |
| 🚚 Migration | ✅ Move sessions between workspaces | ❌ Not available |
| 📋 Dependencies | ✅ Minimal (just Node.js) | ❌ Docker, LanceDB, Ollama, FastAPI |
Key Advantages
- Blazing Fast: No embedding or vectorization step. Reads directly from Cursor's native SQLite database, so results are instant.
- Grep-Style Search: Uses direct text matching instead of vector retrieval. More lightweight, predictable, and stable for most use cases—no hallucinated results, no embedding drift, and exact matches every time.
- Zero Configuration: Run with
npx- no Docker containers, no Python environments, no API keys, no LLM setup. - Works Offline: Everything runs locally without any external services or AI models.
- Data Portability: Full backup, restore, and cross-workspace migration capabilities to keep your chat history safe and portable.
- Lightweight: ~50KB package vs multi-GB Docker images with vector databases.
Installation
No installation required! Run directly via npx:
npx cursor-history-mcp
Configuration
Cursor

Claude Code
Add to your Claude Code MCP settings:
{
"mcpServers": {
"cursor-history": {
"command": "npx",
"args": ["-y", "cursor-history-mcp"]
}
}
}
Claude Desktop
Add to your Claude Desktop configuration (~/.claude/claude_desktop_config.json):
{
"mcpServers": {
"cursor-history": {
"command": "npx",
"args": ["-y", "cursor-history-mcp"]
}
}
}
Available Tools
| Tool | Description |
|---|---|
cursor_history_list |
List chat sessions with metadata |
cursor_history_show |
View full conversation content |
cursor_history_search |
Search across all sessions |
cursor_history_export |
Export session to Markdown or JSON |
cursor_history_backup |
Create backup of all history |
cursor_history_restore |
Restore from backup (destructive) |
cursor_history_migrate |
Move/copy sessions between workspaces (destructive) |
cursor_history_year_pack |
Generate year-in-review data package with stats, topics, and prompt template |
🎆 Year in Review
Generate a personalized annual report from your Cursor AI chat history — discover your coding patterns, favorite topics, and development journey.
What You Get
| 📊 Chat Stats | Total questions, active months, monthly activity |
| 🏷️ Topic Discovery | Auto-detected coding topics and interests |
| 📈 Trend Tracking | How your focus shifted throughout the year |
| 🔑 Keywords | Your most-used terms and phrases |
| 🔒 Privacy Safe | Sensitive data automatically masked |
| 📝 LLM Prompt | Ready-to-use prompt for a polished report |
Try It
- "Generate my 2025 Cursor year in review"
- "Create a year pack for ~/myapp"
- "Generate my 2025 year in review in English"
Usage Examples
After configuring, ask your AI assistant:
- "List my Cursor chat sessions"
- "Show me session #1"
- "Search my Cursor history for 'authentication'"
- "Export session #1 as markdown"
- "Backup my Cursor chat history"
Requirements
- Node.js 20+
- Cursor IDE installed with existing chat history
Contributing
Contributions are welcome! Whether it's bug reports, feature requests, documentation improvements, or code contributions—all PRs and issues are appreciated.
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。