How to Use the HireVue MCP in AutoGen

Q: How do I pass HireVue tools to an AutoGen agent?

Install the autogen-extmcp package. Fetch the tool list using mcpservertools and pass it directly into your AssistantAgent constructor.

Q: Can multiple AutoGen agents share the HireVue MCP tools?

Yes. You can equip a recruiter agent with createinterview and a manager agent with getcandidate. They will coordinate tool usage through their conversational framework.

Deploy multi-agent HR teams that debate hiring decisions and schedule interviews via the AutoGen MCP integration.

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Connect HireVue MCP to AutoGen

Create your Vinkius account to connect HireVue 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 HireVue with AutoGen

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Multi-Agent Recruitment Workflows

AutoGen lets you build MCP workflows where agents challenge each other. You can assign one agent to evaluate a resume and another to check open roles using `list_positions`. They negotiate the fit before proceeding. Once they reach a consensus, a dedicated scheduling agent takes over. It executes `create_candidate` to log the applicant and immediately fires `create_interview`. You get a completely autonomous, peer-reviewed hiring pipeline.

AutoGen Meets HireVue

Connecting this MCP Server is straightforward. You pass the server URL into mcp_server_tools. The McpToolAdapter automatically handles all the schema conversions so your agents know exactly what parameters `get_position` requires. You do not have to mess with complex JSON mapping. The framework translates the tool definitions natively. If an agent needs to pull applicant details, it calls `get_candidate` just like a standard local function.

Handle Scheduling Conflicts

Things go wrong in recruitment. When a video conference fails, your agents can discuss the failure. A coordinator agent can read the error from `get_interview` and instruct a secondary agent to trigger `cancel_interview`. Both agents then work together to find a new time slot and run `update_candidate` with the revised notes. The agents manage the entire error-recovery process through conversation, keeping your actual HR team out of the weeds.

Setup guide

Set up HireVue 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 HireVue 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="HireVue_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent HireVue 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="HireVue_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent HireVue 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 HireVue. 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 HireVue MCP in AutoGen

Install the autogen-ext[mcp] package. Fetch the tool list using mcp_server_tools and pass it directly into your AssistantAgent constructor.

Yes. You can equip a recruiter agent with create_interview and a manager agent with get_candidate. They will coordinate tool usage through their conversational framework.

No. The built-in adapter automatically converts the standard tool definitions into the exact format your conversational agents expect.

The HireVue API returns an error to the chat. The executing agent reads the failure message, corrects its candidate payload based on the feedback, and tries the update_candidate request again.

This MCP Server processes raw applicant resumes, job titles, and interview metadata. Auth is handled entirely on our end. The connection relies on ephemeral, isolated execution environments, meaning your applicant data disappears the moment the agent finishes its task.

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