MCP Server Dataset Builder
Description
# 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…
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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- wanghaisheng
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- Combines data from curated lists and GitHub search
- Automatically assigns categories based on repository content
- Detects programming languages and frameworks used
- Adds emoji indicators for quick visual identification
- Updates daily to keep the dataset current
- Preserves 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 BuilderCommand (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
From the repository
The dataset is automatically updated daily via a GitHub Actions workflow; no manual steps are required. To run locally, install the dependencies (pip install -r requirements.txt) then execute python extract_mcp_servers.py or python daily.py. A manual workflow run can be triggered from the Actions tab, with optional customization of search keywords, minimum stars, and minimum forks.
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"
]
}
}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 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
- 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
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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