How to Use the Wizehire MCP in AutoGen

Q: What if I need to confirm job requirements with Wizehire and AutoGen?

You call getjobdetails so that one agent can use those specifications as facts. Another agent then checks the candidate list against these hard requirements.

Q: Can I check current user permissions with Wizehire and AutoGen?

Yes, an initial call to getcurrentuser allows your agents to understand their own context and limitations before making any decisions on the hiring process.

Q: Is listing all active job postings useful with Wizehire and AutoGen?

Listing them using listactivejobpostings gives every agent a common, up-to-date set of goals to work from. It keeps the debate focused on real needs.

Drive consensus decisions with AutoGen and the Wizehire MCP Server.

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Connect Wizehire MCP to AutoGen

Create your Vinkius account to connect Wizehire 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 Wizehire with AutoGen

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Debate Hiring Decisions using AutoGen

You can set up agents to debate hiring choices. One agent might use `list_candidates` to suggest a top person, while another checks that candidate's eligibility by calling `get_job_details`. They negotiate the final recommendation. It forces consensus-driven decision making, which is exactly what complex HR problems require.

Verify System Status with AutoGen and MCP Server

A governance agent can check system integrity by running `check_api_health` at the start of every session. Another agent might use `list_office_locations` to verify that all proposed jobs align with physical infrastructure. This process adds a layer of automated risk management to your multi-agent conversation.

Multi-Agent Candidate Management

Multiple agents can manage the candidate lifecycle. Agent A uses `create_new_candidate`. Agent B, acting as HR ops, then validates and moves them using `update_candidate_hiring_stage` to ensure proper process flow. It makes the entire recruitment pipeline a collaborative effort.

Setup guide

Set up Wizehire 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 Wizehire 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="Wizehire_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

AutoGen's strength is debate. Multiple agents challenge each other's conclusions—like debating which candidate is best for a role—to reach a final, consensus decision.

You call `get_job_details` so that one agent can use those specifications as facts. Another agent then checks the candidate list against these hard requirements.

Yes, an initial call to `get_current_user` allows your agents to understand their own context and limitations before making any decisions on the hiring process.

The MCP Server handles Candidate records, Job records, and defined Hiring Stage types. These are the core datasets your agents debate over and manipulate.

Listing them using `list_active_job_postings` gives every agent a common, up-to-date set of goals to work from. It keeps the debate focused on real needs.

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