How to Use the PMC Open Access (PubMed Central) MCP in AutoGen

Q: How do AutoGen agents collaborate to query PMC Open Access (PubMed Central)?

You assign one agent to discover articles using oadiscover and another to fetch the metadata via oaigetrecord. They collaborate in a chat to compile the final bibliography.

Q: Can AutoGen agents export bibliographies directly?

Yes. An agent can call exportcitation to generate BibTeX or RIS formats, then write them to a local file once the group approves the list.

Deploy AutoGen agents that debate, verify, and compile PMC Open Access (PubMed Central) medical research.

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Connect PMC Open Access (PubMed Central) MCP to AutoGen

Create your Vinkius account to connect PMC Open Access (PubMed Central) to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup PMC Open Access (PubMed Central) with AutoGen

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Multi-Agent Research Debates via MCP Server

One AutoGen agent can fetch the data while another verifies the citation quality. Using this MCP Server, your AutoGen research agent runs `oai_get_record` to grab paper metadata, while a critic agent analyzes it for potential bias or retraction. The AutoGen agents discuss the findings in a group chat. They only approve the paper for your final report once they reach consensus on its clinical relevance.

Automated ID Translation and Verification

AutoGen agents can split the labor of managing messy medical databases. A database agent detects mismatched citations and passes them to an AutoGen worker agent running `convert_ids`. The worker agent translates PMIDs to PMCIDs and returns the clean data. The AutoGen supervisor agent then runs `export_citation` to generate the final RIS file, ensuring no manual data entry is needed.

Distributed Article Harvesting

Scale up your literature reviews without hitting API blocks in AutoGen. An AutoGen coordinator agent uses `oai_list_identifiers` to segment the target article range into smaller chunks. It distributes these chunks to separate AutoGen worker agents. Each worker runs `oai_list_records` to harvest metadata in parallel, staying within safe rate limits.

Setup guide

Set up PMC Open Access (PubMed Central) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes PMC Open Access (PubMed Central) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="PMC Open Access (PubMed Central)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent PMC Open Access (PubMed Central) data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="PMC Open Access (PubMed Central)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent PMC Open Access (PubMed Central) data")
    print(result.messages[-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by PMC (PubMed Central). All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about PMC Open Access (PubMed Central) MCP in AutoGen

You assign one agent to discover articles using `oa_discover` and another to fetch the metadata via `oai_get_record`. They collaborate in a chat to compile the final bibliography.

Yes. A critic agent can identify broken IDs, then prompt a resolver agent to run `convert_ids` to find the correct PMCID or DOI.

Configure your supervisor agent to track API latency. It can pause worker agents calling `oai_list_records` if it detects rate-limiting responses.

Yes. An agent can call `export_citation` to generate BibTeX or RIS formats, then write them to a local file once the group approves the list.

Your search inputs and PMCID requests pass directly to the NIH servers through an encrypted, stateless Vinkius tunnel. No medical queries or returned metadata are saved or logged on the host.

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