Can I read private repositories?

Yes, provided your Personal Access Token (PAT) has the 'repo' scope or appropriate fine-grained permissions for those repositories.

How do I find a repository owner and name?

In a GitHub URL like `github.com/vinkius/mcp-server`, the owner is `vinkius` and the repository name is `mcp-server`.

Does it support creating pull requests?

This version supports listing pull requests and issues. PR creation is currently handled through the web interface or other specialized tools.

INSTANT PLUG AND PLAY

GitHub MCP Server for CrewAIGive CrewAI instant access to 12 tools to Create New Issue, Get File Content, Get My Profile, and more

Name: GitHub
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to GitHub through Vinkius, pass the Edge URL in the `mcps` parameter and every GitHub tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The GitHub app connector for CrewAI is a standout in the Loved By Devs category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="GitHub Specialist",
    goal="Help users interact with GitHub effectively",
    backstory=(
        "You are an expert at leveraging GitHub tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in GitHub "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About GitHub MCP Server

Connect your GitHub account to any AI agent and take full control of your source control and development workflows through natural conversation.

When paired with CrewAI, GitHub becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call GitHub tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Repository Orchestration — List and manage your repositories programmatically, including retrieving star counts, languages, and detailed metadata
Issue Lifecycle — Monitor project status by listing open issues and creating new ones directly through your agent to maintain momentum
Code Intelligence — Search through repositories and files programmatically to find specific logic and retrieve raw file contents (base64) for analysis
Collaboration Visibility — Monitor pull requests and recent notifications to stay updated on team-wide development activity and code reviews
Resource Management — Access user profiles, organization memberships, and Gists to manage your complete GitHub presence programmatically

The GitHub MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 12 GitHub tools available for CrewAI

When CrewAI connects to GitHub through Vinkius, your AI agent gets direct access to every tool listed below — spanning source-control, repository-management, pull-requests, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_new_issue

Open GitHub issue

get_file_content

Read file from repo

get_my_profile

Get account info

get_repository_details

Get repo info

list_my_gists

List code snippets

list_my_organizations

List user orgs

list_my_repositories

List your GitHub repos

list_pull_requests

List repo PRs

list_recent_notifications

Check GitHub inbox

list_repo_branches

Check repo branches

list_repository_issues

List repo issues

search_repositories

Find GitHub projects

Connect GitHub to CrewAI via MCP

Follow these steps to wire GitHub into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from GitHub

Why Use CrewAI with the GitHub MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with GitHub through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

GitHub + CrewAI Use Cases

Practical scenarios where CrewAI combined with the GitHub MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries GitHub for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries GitHub, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain GitHub tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries GitHub against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for GitHub in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with GitHub immediately.

"List all my GitHub repositories and show their stars count."

"Find all open issues in the repository 'vinkius/mcp-server'."

"Get the content of 'README.md' from repository 'vinkius/mcp-server'."

Troubleshooting GitHub MCP Server with CrewAI

Common issues when connecting GitHub to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

GitHub + CrewAI FAQ

Common questions about integrating GitHub MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.