GitHub MCP Server

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Tài liệu

GitHub MCP — Repo Search, Stats & Compare for AI Agents (nexgendata/github-mcp-server) Actor

MCP server exposing GitHub repo search, stats, language breakdown and comparison as agent tools. Connect Claude, Cursor, n8n or the OpenAI Agents SDK.

Pricing

from $20.00 / 1,000 tool calls

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A".

How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows.

  • AI agents and MCP clients — the Apify MCP server at https://mcp.apify.com (remote, streamable HTTP, OAuth on first use).
  • Agentic workflows and local Actor development — Agent Skills with the Apify CLI: npm install -g apify-cli, then apify login.
  • JavaScript/TypeScript projects — the official JS/TS client: npm install apify-client.
  • Python projects — the official Python client: pip install apify-client.
  • Any other language — the REST API.

For usage examples, see the API section below.

For more details, see Apify documentation as Markdown index and Markdown full-text.

README

GitHub MCP

A Model Context Protocol server that gives AI agents GitHub repository data — search, stats, languages and comparison — as callable tools. For dev-research and OSS-analysis agents.

🛠 Tools (4)

  • compare_repos — Compare two repositories.
  • get_repo_languages — Language breakdown for a repository.
  • get_repo_stats — Stars, forks and activity stats.
  • search_repos — Search GitHub repositories.

🔌 Connect (Claude Desktop / Cursor / n8n / OpenAI Agents SDK)

Add this MCP server to your client config:

{
  "mcpServers": {
    "github": {
      "url": "https://nexgendata--github-mcp-server.apify.actor/mcp"
    }
  }
}

Sample agent prompt:

Compare two frameworks' repos on stars, activity and language breakdown.

Pricing: $0.02 per tool call (Pay-Per-Event). Runs in Standby mode.

Related NexGenData MCP servers & developer-tools actors

Use caseActor
Developer tools MCP (NPM, PyPI, Stack Overflow)developer-tools-mcp-server
Web-scraping MCP (any URL, AI agents)web-scraping-mcp-server
SEO & web analysis MCPseo-web-analysis-mcp-server
Domain intelligence MCPdomain-intelligence-mcp-server
News MCP (Hacker News + tech press)news-mcp-server
Reddit MCP (r/programming, r/MachineLearning)reddit-mcp-server
YouTube / media MCP (DevRel videos)youtube-media-mcp-server
Academic research MCP (arxiv + papers)academic-research-mcp-server
26-server gateway (GitHub + 25 more)enterprise-mcp-gateway

Built and maintained by NexGenData. Home: thenextgennexus.com

Actor input Schema

Actor input object example

{}

API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

JavaScript example

import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("nexgendata/github-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

Python example

from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("nexgendata/github-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

CLI example

echo '{}' |
apify call nexgendata/github-mcp-server --silent --output-dataset

MCP server setup

{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgendata/github-mcp-server"
        }
    }
}

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an Authorization: Bearer <APIFY_API_TOKEN> header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/TtAI8dvxRH4ji375T/builds/UBaYui7xukYggEfdV/openapi.json