MCP Server Dataset Builder

by wanghaisheng

193 downloads Not rated yet

GitHub

About

# MCP Server Dataset Builder A comprehensive tool for building and maintaining a dataset of Model Context Protocol (MCP) servers. This tool automatically collects, categorizes, and updates information about MCP servers from multiple sources. ## Overview The MCP Server Dataset Builder is designed to: 1. Extract MCP…

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- Dual Data Sources: Combines data from curated lists and GitHub search
- Automatic Categorization: Assigns categories based on repository content
- Tech Stack Detection: Identifies programming languages and frameworks
- Emoji Tagging: Adds visual indicators for quick identification
- Daily Updates: Automatically runs to keep the dataset current
- Data Persistence: Maintains historical data while adding new entries

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name MCP Server Dataset Builder

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

From the repository

pip install -r requirements.txt

The following environment variables can be used to customize the behavior:

| Variable | Description | Default |
|----------|-------------|---------|
| GITHUB_TOKEN | GitHub API token for authentication | - |
| KEYWORDS_ENV | Comma-separated list of search keywords | MCP-related keywords |
| MIN_STARS | Minimum number of stars for repositories | 10 |
| MIN_FORKS | Minimum number of forks for repositories | 5 |

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "mcp server dataset builder": {
            "mcp-server-dataset": {
                "command": "python",
                "args": [
                    "extract_mcp_servers.py"
                ]
            }
        }
    }
}

McpServers

{
    "mcp-server-dataset": {
        "command": "python",
        "args": [
            "extract_mcp_servers.py"
        ]
    }
}

A comprehensive tool for building and maintaining a dataset of Model Context Protocol (MCP) servers. This tool automatically collects, categorizes, and updates information about MCP servers from multiple sources.

Overview

The MCP Server Dataset Builder is designed to:

1. Extract MCP server information from the awesome-mcp-servers repository
2. Search GitHub for additional MCP server repositories
3. Merge and deduplicate data from both sources
4. Generate a daily CSV file with comprehensive information about each server

Features

Dataset Structure

The generated CSV files contain the following fields:

| Field | Description |
|-------|-------------|
| name | Repository name |
| description | Repository description |
| html_url | URL to the repository |
| stars | Number of GitHub stars |
| forks | Number of GitHub forks |
| keywords | Comma-separated list of keywords |
| category | Primary category (e.g., framework, utility, client) |
| techstack | Comma-separated list of technologies used |
| emojis | Visual indicators for quick identification |

Usage

Automatic Daily Updates

The dataset is automatically updated daily via GitHub Actions. No manual intervention is required.

Manual Trigger

You can manually trigger the workflow from the GitHub Actions tab:

1. Go to the "Actions" tab in the repository
2. Select "Unified MCP Servers Extraction"
3. Click "Run workflow"
4. Optionally customize:
- Keywords for GitHub search
- Minimum stars and forks thresholds
- Which extraction methods to run

Local Development

To run the scripts locally:

```bash

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About

Explore

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Overview

Features

Dataset Structure

Usage

Automatic Daily Updates

Manual Trigger

Local Development

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