How to Use the Guru MCP in OpenAI Agents SDK

Q: Can I use Guru to track my team with OpenAI Agents SDK?

You can. Use listworkspacemembers to pull team data and cross-reference it with specific knowledge cards.

Plug your Guru knowledge base directly into OpenAI Agents SDK for production-grade, validated agent workflows.

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Connect Guru MCP to OpenAI Agents SDK

Create your Vinkius account to connect Guru 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 Guru with OpenAI Agents SDK

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Instant knowledge access for OpenAI Agents SDK

Your agent pulls context directly from your wiki without leaving the terminal. Use `search_knowledge_base` to grab relevant snippets before the agent drafts a response. This keeps your model grounded in actual company data. It stops the guessing game and gives your agent the specific card details it needs to answer questions accurately.

Automated card management via MCP Server

Stop manually updating documentation. Your agent uses `create_knowledge_card` and `update_knowledge_card` to document decisions or project specs as they happen. Everything stays in sync while the agent works. You get a living record of your development process without the overhead of manual entry.

Production health checks for agents

Verify your integration instantly with `verify_api_connection`. It prevents runtime failures by confirming your credentials and endpoint status before any heavy lifting starts. This is essential for your OpenAI Agents SDK pipeline. It ensures your agent is always talking to the live wiki, not a stale cache.

Setup guide

Set up Guru 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 Guru tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Guru 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="Guru Agent",
            instructions="You have access to Guru 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 Guru MCP in OpenAI Agents SDK

It gives your agent a direct line to your internal documentation. By using `search_knowledge_base`, the agent finds the exact info it needs to avoid hallucinations.

Yes. The server handles all authentication, so your agent stays focused on logic. Just call `verify_api_connection` to ensure the link is solid.

You can. Use `list_workspace_members` to pull team data and cross-reference it with specific knowledge cards.

The server provides raw output. You should handle the data in your agent logic to ensure your OpenAI Agents SDK workflow remains stable.

We use scoped tokens to limit what your agent can see. The server only touches the knowledge cards and collection metadata you explicitly allow it to access.

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