local-history-mcp
MCP server for accessing VS Code/Cursor's Local History
Local History MCP Server
Access Cursor/VS Code Local History through the Model Context Protocol for AI-powered data recovery
Overview
This MCP server bridges the gap between AI assistants and editor Local History, enabling data recovery and enhanced context awareness. Unlike undo/redo, Local History captures file snapshots at save points, preserving work that would otherwise be lost.
Problem: Current AI assistants (Claude, Cursor AI, GitHub Copilot) cannot access Local History data despite having extensive diagnostic capabilities.
Solution: Simple MCP server providing direct access to Cursor/VS Code Local History for personal use.
Installation
Option 1: Package Manager (Recommended)
Install using your preferred package manager:
# npm
npx local-history-mcp
# pnpm
pnpm dlx local-history-mcp
# yarn
yarn global add local-history-mcp
# bun
bunx local-history-mcp
Option 2: From Source
git clone https://github.com/xxczaki/local-history-mcp.git && cd local-history-mcp
pnpm install
pnpm build
pnpm start
MCP Tools
| Tool | Description |
|---|---|
list_history_files |
List all files with Local History |
get_file_history |
View complete history for a file |
get_history_entry |
Get specific history entry content |
restore_from_history |
Restore file to previous state (with backup) |
search_history_content |
Search across all history entries |
get_history_stats |
Overview statistics |
Configuration
Cursor
You can install this MCP server in Cursor using the one-click install button:
Or manually configure by following the official Cursor MCP documentation.
Claude Code & Claude Desktop
For Claude Code (CLI), install directly:
claude mcp add local-history -- npx -y local-history-mcp
For Claude Desktop, see the official MCP documentation.
VS Code
See the official documentation.
Development
# Development mode
pnpm dev
# Run tests
pnpm test
# Linting and formatting
pnpm lint
# Launch MCP Inspector
pnpm inspector
AI disclosure
This project contains code generated by Large Language Models (LLMs), under human supervision and proofreading.
License
MIT
Yorumlar (0)
Yorum birakmak icin giris yap.
Yorum birakSonuc bulunamadi