Fetch Kit

A Go-based MCP (Model Control Protocol) connector that enables AI assistants like Claude to interact with web services. This tool provides a seamless interface for AI models to perform various web-related operations.

Features

• Retrieve web content using Jina AI
• Leverage Google AI (Gemini) services
• Support for various web service integrations
• Configurable tool groups
• Interact with web services through AI models

Installation

Requirements: Go 1.23.2+ (for building from source)

There are several ways to install Fetch Kit:

Option 1: Download from GitHub Releases

1. Visit the GitHub Releases page
2. Download the binary for your platform:
   • fetch-kit_linux_amd64 for Linux
   • fetch-kit_darwin_amd64 for macOS
   • fetch-kit_windows_amd64.exe for Windows
3. Make the binary executable (Linux/macOS):

   chmod +x fetch-kit_*
   

4. Move it to your PATH (Linux/macOS):

   sudo mv fetch-kit_* /usr/local/bin/fetch-kit
   

Option 2: Go Install

go install github.com/nguyenvanduocit/fetch-kit@latest

Option 3: Docker

Using Docker directly

1. Pull the pre-built image from GitHub Container Registry:

   docker pull ghcr.io/nguyenvanduocit/fetch-kit:latest

2. Or build the Docker image locally:

   docker build -t fetch-kit .

Configuration

Environment Variables

The following environment variables are used for configuration:

# Required for AI services
GOOGLE_AI_API_KEY=    # Required: API key for Google AI (Gemini) service
JINA_API_KEY=         # Required: API key for Jina AI service

# Optional configurations
ENABLE_TOOLS=         # Optional: Comma-separated list of tool groups to enable (empty = all enabled)
PROXY_URL=            # Optional: HTTP/HTTPS proxy URL if needed

You can set these:

1. Directly in the Docker run command (recommended)
2. Through a .env file (use the -env flag)
3. Directly in your shell environment

Using with Claude and Cursor

To make Fetch Kit work with Claude and Cursor, you need to add configuration to your Cursor settings.

Step 1: Install Fetch Kit

Choose one of the installation methods above (Docker recommended).

Step 2: Configure Cursor

1. Open Cursor
2. Go to Settings > MCP > Add MCP Server
3. Add the following configuration:

Option A: Using Docker (Recommended)

{
  "mcpServers": {
    "fetch_kit": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e", "GOOGLE_AI_API_KEY=your_google_ai_key",
        "-e", "JINA_API_KEY=your_jina_api_key",
        "ghcr.io/nguyenvanduocit/fetch-kit:latest"
      ]
    }
  }
}

Option B: Using Local Binary

{
  "mcpServers": {
    "fetch_kit": {
      "command": "fetch-kit",
      "args": ["-env", "/path/to/.env"]
    }
  }
}

Step 3: Test Connection

You can test if the connection is working by asking Claude in Cursor:

@fetch_kit get web content from https://example.com

Enable Tools

Fetch Kit supports various tool groups that can be enabled or disabled using the ENABLE_TOOLS environment variable. If not specified, all tools are enabled by default.

CLI Usage

In addition to the MCP server, fetch-kit ships a standalone CLI binary (fetch-cli) for direct terminal use — no MCP client needed.

Installation

# Build locally
just install-cli

# Or with Go
go install github.com/nguyenvanduocit/fetch-kit/cmd/fetch-cli@latest

Quick Start

# Set credentials (only needed for the tools you use)
export JINA_API_KEY=your-jina-key
export GOOGLE_AI_API_KEY=your-gemini-key

# Or use a .env file
fetch-cli --env .env <command> [flags]

Commands

Command	Description
jina-fetch	Fetch and extract web content via Jina AI
gemini-fetch	Fetch and analyze content using Gemini AI
youtube	Get YouTube video transcripts

Examples

# Fetch a web page
fetch-cli jina-fetch --url https://example.com

# Ask Gemini about a URL
fetch-cli gemini-fetch --question "Summarize this" --context "https://example.com"

# Get YouTube transcript
fetch-cli youtube --video-id dQw4w9WgXcQ

# JSON output
fetch-cli jina-fetch --url https://example.com --output json

Flags

Every command accepts:

• --env string — Path to .env file (default: .env)
• --output string — Output format: text (default) or json

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

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For a list of recent changes, see CHANGELOG.md.

Installation

Homebrew (macOS/Linux)

brew install nguyenvanduocit/tap/fetch-kit