Forgejo (Gitea Fork) MCP Server for CrewAIGive CrewAI instant access to 4 tools to Create Token, Dispatch Workflow, Get Forgejo Version, and more

Name: Forgejo (Gitea Fork)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Forgejo (Gitea Fork) MCP Server for CrewAI is a standout in the Loved By Devs category — giving your AI agent 4 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Forgejo (Gitea Fork) Specialist",
    goal="Help users interact with Forgejo (Gitea Fork) effectively",
    backstory=(
        "You are an expert at leveraging Forgejo (Gitea Fork) 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 Forgejo (Gitea Fork) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 available tools "
        "and what they can do."
    ),
)

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

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About Forgejo (Gitea Fork) MCP Server

Connect your Forgejo or Gitea instance to any AI agent to streamline your DevOps and repository management workflows through natural conversation.

When paired with CrewAI, Forgejo (Gitea Fork) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Forgejo (Gitea Fork) 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

Version Auditing — Retrieve detailed Forgejo and Gitea-compatible version information to ensure API compatibility across your infrastructure.
Token Management — Generate new Personal Access Tokens (PATs) with specific scopes (read/write) using your BasicAuth credentials.
CI/CD Automation — Trigger manual workflow dispatches for Forgejo Actions directly from the chat to start builds or deployments.
Instance Inspection — Verify the health and configuration of your self-hosted Git service without leaving your development environment.

The Forgejo (Gitea Fork) MCP Server exposes 4 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 4 Forgejo (Gitea Fork) tools available for CrewAI

When CrewAI connects to Forgejo (Gitea Fork) through Vinkius, your AI agent gets direct access to every tool listed below — spanning git-repository, self-hosted, version-control, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

create

Create token on Forgejo (Gitea Fork)

Generates a new personal access token. Generate a new API token for a user

dispatch

Dispatch workflow on Forgejo (Gitea Fork)

Trigger a manual workflow dispatch in Forgejo Actions

get

Get forgejo version on Forgejo (Gitea Fork)

Get detailed Forgejo version information

get

Get gitea version on Forgejo (Gitea Fork)

Get the Gitea-compatible version of the Forgejo instance

Connect Forgejo (Gitea Fork) to CrewAI via MCP

Follow these steps to wire Forgejo (Gitea Fork) into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind 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 4 tools from Forgejo (Gitea Fork)

Why Use CrewAI with the Forgejo (Gitea Fork) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Forgejo (Gitea Fork) 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

Forgejo (Gitea Fork) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Forgejo (Gitea Fork) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Forgejo (Gitea Fork) 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 Forgejo (Gitea Fork), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Forgejo (Gitea Fork) 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 Forgejo (Gitea Fork) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Forgejo (Gitea Fork) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Forgejo (Gitea Fork) immediately.

"Check the Forgejo and Gitea-compatible versions of my instance."

"Generate a new API token named 'CI-Runner' with read:repository scope for user 'admin'."

"Trigger the 'deploy.yaml' workflow in the 'main-app' repository owned by 'dev-team'."

Troubleshooting Forgejo (Gitea Fork) MCP Server with CrewAI

Common issues when connecting Forgejo (Gitea Fork) to CrewAI through 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.

Forgejo (Gitea Fork) + CrewAI FAQ

Common questions about integrating Forgejo (Gitea Fork) 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.