What is Mcp Vibe Tools

mcp-vibe-tools is an MCP server wrapper for vibe-tools, enabling AI interaction without the need for command line interface (CLI) usage. It allows AI agents and services to communicate with vibe-tools seamlessly.

Use cases

Use cases include automating project management tasks, enabling AI-driven interactions with development tools, and facilitating seamless integration of AI agents into existing workflows.

How to use

To use mcp-vibe-tools, install the required Python dependencies and the vibe-tools CLI. Start the MCP server, and then send JSON requests to the server endpoints corresponding to various vibe-tools commands.

Key features

Key features include wrapping all vibe-tools commands, dynamically managing execution context (working directory), parameter mapping from JSON to CLI flags, async tool support, and unit tests for core functionality.

Where to use

mcp-vibe-tools can be used in software development environments where AI agents need to interact with project management tools, particularly those utilizing vibe-tools for various tasks.

mcp-vibe-tools

mcp server wrapper for cursor-tools (now vibe-tools).

This project provides an MCP (Model Context Protocol) server built with MCP Python SDK that wraps the vibe-tools CLI (formerly cursor-tools), allowing AI agents or other services (like Claude Desktop) to interact with vibe-tools without using the command line directly…

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Table of Contents

• Overview
• Features
• Prerequisites
• Installation
• Running the Server
• Environment Variables
• Available MCP Tools
• Development
• Contributing
• License

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Overview

This server exposes endpoints corresponding to various vibe-tools commands (like repo, plan, web, browser, xcode, etc.). It translates JSON request bodies into CLI arguments, executes the command in the correct working directory, and returns the output.

It is implemented in Python using Python MCP SDK (https://github.com/modelcontextprotocol/python-sdk).

A key feature is the ability to dynamically set the working directory for context-dependent commands, enabling interaction with multiple projects without restarting the server.

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Features

• Wraps ALL vibe-tools commands.
• Manages execution context (working directory) dynamically.
• Allows changing the target project directory via an MCP tool.
• Handles parameter mapping from JSON to CLI flags.
• Provides async tool support with proper context injection.
• Includes unit tests for core functionality.

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Prerequisites

1. Python 3.11+

2. vibe-tools CLI

   • Must be installed globally (npm install -g vibe-tools or pnpm install -g vibe-tools)
   • Properly configured with API keys, .repomixignore, etc.
   • See vibe-tools repo

3. Install Python dependencies

pip install -r requirements.txt

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Installation

The recommended way to install mcp-vibe-tools is using uv:

uv tool install mcp-vibe-tools

This will install the CLI entry point mcp-vibe-tools into your uv tool environment.

You can then run the server with:

uv run mcp-vibe-tools

Make sure you have the vibe-tools CLI installed globally via npm or pnpm:

npm install -g vibe-tools

Important: Set the environment variable VIBE_TOOLS_PATH to the absolute path of your vibe-tools binary (usually something like /usr/local/bin/vibe-tools):

export VIBE_TOOLS_PATH=/absolute/path/to/vibe-tools

Example mcp.json configuration

Add this block to your MCP client’s configuration to connect:

{
  "mcpServers": {
    "vibe-tools": {
      "name": "uv",
      "args": [
        "run",
        "mcp-vibe-tools"
      ],
      "env": {
        "VIBE_TOOLS_PATH": "/absolute/path/to/vibe-tools"
      }
    }
  }
}

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Running the Server

Start the FastMCP server:

uv run mcp-vibe-tools

Environment Variables

• VIBE_TOOLS_PATH (preferred): Absolute path or command name for the vibe-tools CLI executable.
• CURSOR_TOOLS_PATH (legacy, still supported): Same as above.
• If both are set, VIBE_TOOLS_PATH takes precedence.
• If neither is set, defaults to 'cursor-tools' (or 'vibe-tools' if aliased).

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Available MCP Tools

ask

Ask any AI model a direct question.
Parameters:

• query (string): The question to ask.
• --provider (string): AI provider (openai, anthropic, perplexity, gemini, modelbox, openrouter).
• --model (string, required): Model to use.
• --reasoning-effort (low|medium|high): Depth of reasoning.

plan

Generate a focused implementation plan using AI.
Parameters:

• query (string): The task or feature to plan.
• --fileProvider (string): Provider for file identification.
• --thinkingProvider (string): Provider for plan generation.
• --fileModel (string): Model for file identification.
• --thinkingModel (string): Model for plan generation.

repo

Ask questions about the current repository context.
Parameters:

• query (string): The question about the repo.
• --subdir (string): Subdirectory to analyze.
• --from-github (string): Remote GitHub repo to analyze.
• --provider (string): AI provider.
• --model (string): Model to use.

web

Perform web search or autonomous web agent queries.
Parameters:

• query (string): The question or search task.
• --provider (string): AI provider.

doc

Generate comprehensive documentation for the repository.
Parameters:

• --from-github (string): Remote GitHub repo.
• --provider (string): AI provider.
• --model (string): Model to use.

youtube

Analyze YouTube videos (summarize, transcript, plan, review).
Parameters:

• url (string): YouTube video URL.
• question (string, optional): Specific question.
• --type (summary|transcript|plan|review|custom): Type of analysis.

github pr

Get information about GitHub pull requests.
Parameters:

• number (int, optional): PR number. If omitted, fetches recent PRs.
• --from-github (string): Remote GitHub repo.

github issue

Get information about GitHub issues.
Parameters:

• number (int, optional): Issue number. If omitted, fetches recent issues.
• --from-github (string): Remote GitHub repo.

clickup task

Get detailed information about a ClickUp task.
Parameters:

• task_id (string): ClickUp task ID.

mcp search

Search the MCP marketplace for available servers.
Parameters:

• query (string): Search query.

mcp run

Run a tool on a connected MCP server.
Parameters:

• query (string): Natural language command specifying the tool and arguments.
• --provider (string): AI provider.

browser act

Automate browser actions (click, type, etc.).
Parameters:

• instruction (string): Natural language instructions.
• --url (string): URL or ‘current’/‘reload-current’.
• --video (string): Directory to save video recording.
• --screenshot (string): Path to save screenshot.

browser observe

Observe interactive elements on a webpage.
Parameters:

• instruction (string): What to observe.
• --url (string): URL or ‘current’/‘reload-current’.

browser extract

Extract data from a webpage.
Parameters:

• instruction (string): What to extract.
• --url (string): URL or ‘current’/‘reload-current’.

xcode build

Build an Xcode project.
Parameters:

• --buildPath (string): Custom build directory.
• --destination (string): Simulator destination.

xcode run

Build and run an Xcode project on a simulator.
Parameters:

• --destination (string): Simulator destination.

xcode lint

Run static analysis on an Xcode project.
No parameters.

set_working_directory

Change the working directory for subsequent commands.
Parameters:

• directoryPath (string): Absolute path to the new working directory.

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Contributing

Contributions welcome! Please open issues or pull requests.

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License

MIT License.