How to Use the Macaulay Library MCP in OpenAI Agents SDK

Q: How do I connect this MCP Server to the OpenAI Agents SDK for the Macaulay Library?

Install openai-agents via pip. Create an MCPServerStreamableHttp instance with your endpoint URL and pass it to your agent's constructor. The SDK auto-discovers the tools immediately.

Q: Can the OpenAI Agents SDK search for specific birds in the Macaulay Library?

Yes. Your agent calls searchmedia with specific parameters to find audio or video files. Set cacheToolsList=True during setup to speed up the tool discovery process.

Q: Does the Macaulay Library work with OpenAI Agents SDK handoffs?

It does. You can have a research agent run getrecentmedia to find new uploads, then hand off the asset IDs to a processing agent. The second agent then calls getasset to pull the exact metadata.

Build production-ready ornithology agents with the OpenAI Agents SDK by connecting directly to the world's largest wildlife media archive.

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Connect Macaulay Library MCP to OpenAI Agents SDK

Create your Vinkius account to connect Macaulay Library 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 Macaulay Library with OpenAI Agents SDK

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Search wildlife media via OpenAI Agents SDK

`search_media` finds specific animal sounds and videos across the entire archive. Your agent passes species parameters and receives matching records without you writing custom API wrappers. You define the search criteria for a specific bird call, and the SDK handles the execution. Built-in guardrails validate the agent's query before it fires, keeping your production logs clean from hallucinated species requests.

Track recent biodiversity uploads

`get_recent_media` pulls the latest wildlife media submissions directly into your pipeline. Your agent reads these fresh records to monitor current birding activity or geographic trends. This MCP Server feeds raw upload data straight to your specialized agents. You can configure handoffs so one agent fetches the recent regional data while another analyzes the results.

Extract exact asset metadata

`get_asset` retrieves the granular details for a specific recording or video. You provide the asset ID, and the tool returns equipment used, location data, and recording quality scores. Tracing in the OpenAI dashboard shows exactly when your agent requested this metadata. You see the exact payload the MCP fetched, making debugging straightforward when building complex ecological data pipelines.

Setup guide

Set up Macaulay Library 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 Macaulay Library tools at runtime.
3

Create your Agent

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

Run the agent

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

Install `openai-agents` via pip. Create an `MCPServerStreamableHttp` instance with your endpoint URL and pass it to your agent's constructor. The SDK auto-discovers the tools immediately.

Yes. Your agent calls `search_media` with specific parameters to find audio or video files. Set `cacheToolsList=True` during setup to speed up the tool discovery process.

It does. You can have a research agent run `get_recent_media` to find new uploads, then hand off the asset IDs to a processing agent. The second agent then calls `get_asset` to pull the exact metadata.

The SDK's tracing catches the error. You can view the exact request payload in your OpenAI dashboard to see if the agent hallucinated a parameter for the search query.

The server only accesses public animal sounds, videos, and user-submitted metadata like recording locations. Your endpoint token authenticates the connection, ensuring zero-trust, ephemeral data access without exposing your core infrastructure.

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