GitHub MCP Server

การวิเคราะห์ repository, issues, pull requests และการสำรวจโครงสร้างโค้ด

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เอกสาร

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/actors/running/actors-in-store.md#pay-per-event

What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the API section below.

Each client library has reference documentation the quickstart does not restate: JavaScript/TypeScript (npm install apify-client) and Python (pip install apify-client).

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.

📊 Sample Output

This actor runs as a standby MCP server: it starts, answers tool calls at its /mcp endpoint and writes no dataset rows, so there is no row table to show. See the tool list and the sample inputs below.

🔧 Input reference

FieldTypeDefaultWhat it does
enableServer (required)booleantrueEnable MCP server mode
portinteger5000Port for MCP server

💰 Pricing

EventPrice (USD)When it is charged
Actor Start (apify-actor-start)$5e-05Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event).
Tool call (tool-call)$0.02Per-tool invocation via MCP Standby

Pay-per-event: you pay only for what the run delivers. A run that delivers nothing bills no result events (only the actor-start event, when the actor defines one). Example: a run that delivers 100 results costs 100 × $0.02 = $2.00 plus the start fee.

🔗 Related Actors

More from the NexGenData MCP servers for AI agents family:

29 more in this family on the NexGenData Store page.

🛠 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/XYsho5FagEo2Q7m8D/openapi.json