How to Use the Modrinth MCP in OpenAI Agents SDK

Q: How do I search for mods on Modrinth using the OpenAI Agents SDK?

Just pass your criteria to the searchprojects tool. Your agent will return a list of matching projects directly from the Modrinth API.

Q: Does this MCP Server handle large dependency trees for OpenAI Agents SDK projects?

It does, but you should use the getprojectdependencies tool with caution. It fetches the full tree, so ensure your agent has enough memory to process the returned list.

Q: Can I verify project authorship through Modrinth when using OpenAI Agents SDK?

Yes, use getteammembers or getuserprofile to check who is behind a project. This helps you confirm the source before your agent pulls any code.

Connect your OpenAI Agents SDK to the Modrinth database to fetch mod metadata and dependency trees in your production workflows.

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Connect Modrinth MCP to OpenAI Agents SDK

Create your Vinkius account to connect Modrinth to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Modrinth with OpenAI Agents SDK

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Automated project discovery with OpenAI Agents SDK

Stop hunting for mod IDs manually. Your agent uses `search_projects` to find exactly what you need based on game version or loader requirements. It pulls the data directly into your agent's context, ensuring your build scripts always reference accurate, current project metadata.

Recursive dependency mapping for modpack builds

Avoid broken builds by letting your agent traverse the dependency graph. The `get_project_dependencies` tool maps out requirements before you start the installation process. Your production agent validates these links in real-time, preventing the common headache of missing files or incompatible versions.

Safe version tracking and team verification

Verify that your project sources are legitimate by checking team member credentials via `get_team_members` within your agent pipeline. The `get_version` tool ensures your agent grabs the specific file hash and release type you need, keeping your deployment environment stable and predictable.

Setup guide

Set up Modrinth MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Modrinth tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Modrinth tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Modrinth tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Modrinth Agent",
            instructions="You have access to Modrinth tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Modrinth MCP in OpenAI Agents SDK

Just pass your criteria to the `search_projects` tool. Your agent will return a list of matching projects directly from the Modrinth API.

It does, but you should use the `get_project_dependencies` tool with caution. It fetches the full tree, so ensure your agent has enough memory to process the returned list.

Yes, use `get_team_members` or `get_user_profile` to check who is behind a project. This helps you confirm the source before your agent pulls any code.

The server will return an error code. You should implement a retry strategy or caching logic in your agent to handle these temporary blocks.

The server only touches public project metadata. No private keys or user credentials are exchanged; your agent only sees what is available on the public API.

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