How to Use the Glean MCP in OpenAI Agents SDK

Q: How do I handle pagination when searching Glean with OpenAI Agents SDK?

The agent uses listcollections or getcollection to navigate structured folders step by step. This prevents your OpenAI Agents SDK pipelines from hitting token limits on massive query returns.

Feed Glean enterprise search directly into your production OpenAI Agents SDK pipelines with zero config.

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Connect Glean MCP to OpenAI Agents SDK

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

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Safe Enterprise Search for OpenAI Agents SDK

Let your production OpenAI Agents SDK pipelines search Glean company knowledge without losing control. This MCP Server exposes tools like `search` and `search_by_datasource` directly to your OpenAI Agents SDK runtime. Built-in OpenAI Agents SDK guardrails validate every Glean query before execution, protecting your corporate index. If a Glean tool call fails, your OpenAI Agents SDK pipeline safely halts or hands off to a human. You get clean Glean search results from Confluence or Slack, fully tracked on your OpenAI Agents SDK dashboard.

Instant Indexing and Document Control

Keep your OpenAI Agents SDK context window fresh by managing Glean documents in real-time. Your OpenAI Agents SDK pipelines use `index_document` and `bulk_index_documents` to push data directly into your Glean index. When files go stale, your OpenAI Agents SDK system calls `delete_document` to purge them from Glean. This active Glean indexing prevents stale context errors in your OpenAI Agents SDK runs. You control exactly what gets written back to the Glean index, keeping your OpenAI Agents SDK search pool clean.

Directory Lookups and Status Checks

Before executing complex OpenAI Agents SDK handoffs, verify your Glean MCP Server health. Your OpenAI Agents SDK system runs `check_glean_status` to confirm Glean is online. Once verified, your OpenAI Agents SDK agent uses `search_people` to route tasks to the right Glean-indexed expert. This setup ensures your OpenAI Agents SDK system never hangs waiting on a dead Glean API. It uses live Glean directory data to resolve OpenAI Agents SDK ownership issues.

Setup guide

Set up Glean 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 Glean tools at runtime.
3

Create your Agent

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

Run the agent

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

You pass the server connection as an MCP server parameter during agent initialization. The SDK automatically reads the schema and registers tools like `search` and `chat` as active agent functions.

Yes, you control this at the server transport layer or via the agent's constructor. You can limit the agent to read-only actions like `search_by_datasource` and block write actions like `delete_document`.

The SDK catches the failure and returns the error trace to your dashboard. You can configure a fallback agent to run `check_glean_status` to see if the issue is network-related.

The agent uses `list_collections` or `get_collection` to navigate structured folders step by step. This prevents your OpenAI Agents SDK pipelines from hitting token limits on massive query returns.

All search queries and indexed document payloads are processed inside Vinkius's isolated MCP sandbox. The server never stores your private Confluence or Slack content, and only the raw JSON results from `search` are passed back to your OpenAI Agents SDK runtime.

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