How to Use the CATS ATS MCP in AutoGen

Q: How do I install the CATS ATS integration for AutoGen?

Grab the autogen-extmcp package from pip. Point mcpservertools at your Vinkius HTTP endpoint, and pass the resulting list straight into your AssistantAgent constructor.

Q: How does AutoGen handle CATS ATS tool schemas?

The McpToolAdapter handles the translation automatically. You never have to manually map ATS endpoints to AutoGen's internal function calling format.

Build debating recruiter agents by hooking the CATS ATS MCP Server into your AutoGen workflows.

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Connect CATS ATS MCP to AutoGen

Create your Vinkius account to connect CATS ATS to AutoGen 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 CATS ATS with AutoGen

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Multi-Agent Candidate Review

`search_candidates` allows your AutoGen squad to pull targeted lists of applicants for group review. A sourcing agent runs the query and passes the results to a technical evaluation agent. These agents debate the merits of each profile. One pushes for hard skills while another checks for culture fit based on past interview notes, eventually converging on a final shortlist.

Recruitment Activity Audits

`list_recruitment_activities` gives your compliance agent direct MCP access to recruiter logs. It scans the timeline to ensure no candidate sits in a stage for too long without feedback. If the agent spots a bottleneck, it flags the issue to a manager agent. They negotiate the priority of the delay and generate a summary report of stalled applications.

Deep Job Context via MCP

`get_candidate_details` paired with `get_job_details` feeds raw, unfiltered data into the conversation. The agents compare the deep specs of the role against the full history of the applicant. Because AutoGen relies on consensus, this detailed data prevents superficial matching. The agents argue over specific bullet points in the job order until they agree on a recommendation.

Setup guide

Set up CATS ATS 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 CATS ATS 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="CATS ATS_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent CATS ATS data")
print(result.messages[-1].content)

Get your connection token →

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="CATS ATS_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent CATS ATS data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CATS ATS. 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 CATS ATS MCP in AutoGen

Grab the `autogen-ext[mcp]` package from pip. Point `mcp_server_tools` at your Vinkius HTTP endpoint, and pass the resulting list straight into your `AssistantAgent` constructor.

The `McpToolAdapter` handles the translation automatically. You never have to manually map ATS endpoints to AutoGen's internal function calling format.

They share the same tool definitions but call them independently. A sourcer might run a wide search while a screener fetches specific candidate details in parallel.

We recommend Streamable HTTP for cloud deployments. It keeps the connection stable while agents deliberate over large candidate datasets.

Vinkius processes all API traffic through isolated sandboxes. Private recruiter notes, candidate addresses, and client company data are wiped from memory the moment the HTTP request completes. No data persists on our infrastructure.

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