How to Use the JobScore MCP in AutoGen

Q: How do AutoGen agents access the JobScore MCP Server?

Configure the mcpservertools with your Vinkius HTTP URL and pass the resulting tool list to your AssistantAgent. The adapter automatically maps the schemas for the agents to use.

Q: How do AutoGen agents resolve conflicting JobScore data?

The agents debate the outputs of tools like getcandidate and getjob. If a candidate's stage does not match the job's open status, the agents will flag this discrepancy in their chat logs.

Let your AutoGen agents debate and coordinate on JobScore candidate evaluations.

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Create your Vinkius account to connect JobScore 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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Coordinate Candidate Screening via Multi-Agent Debate

The `get_candidate` tool delivers deep application histories and resume highlights directly to your AutoGen agent conversation. One AutoGen agent can analyze candidate qualifications while another flags potential scheduling conflicts based on the contact history. Because these AutoGen agents debate, they challenge each other's interpretations of the candidate's status. They use the raw JobScore data returned by the API to reach a consensus before recommending the next interview step.

Align Job Requirements with Hiring Teams

The `get_job` tool provides the detailed requirements and hiring team identifiers that your AutoGen agents need to resolve staffing disputes. An AutoGen recruiting agent can cross-reference these requirements with candidate profiles fetched from the API. By calling `list_hiring_teams`, your AutoGen group chat identifies the exact managers responsible for the role. The AutoGen agents then draft targeted updates for those specific team members, ensuring everyone stays aligned on hiring priorities.

Map Recruiting Channels Using the AutoGen MCP Server

The `list_sources` tool exposes where your candidates are originating, allowing your AutoGen agents to analyze channel effectiveness. A performance agent can debate budget allocations with a sourcing agent based on this real-time JobScore data. Using `list_jobs` alongside source data lets your AutoGen agents identify which platforms yield the best candidates for specific roles. They negotiate the best sourcing strategy, citing hard metrics pulled directly from your JobScore account.

Setup guide

Set up JobScore 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 JobScore 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="JobScore_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Configure the mcp_server_tools with your Vinkius HTTP URL and pass the resulting tool list to your AssistantAgent. The adapter automatically maps the schemas for the agents to use.

Yes, different agents in your group chat can call different tools like `list_candidates` or `list_users` as they discuss hiring metrics. The framework manages the tool execution sequence during the conversation.

The agents debate the outputs of tools like `get_candidate` and `get_job`. If a candidate's stage does not match the job's open status, the agents will flag this discrepancy in their chat logs.

Yes, you can connect your agents using either transport method. Vinkius provides a secure HTTP endpoint, which is ideal for distributed AutoGen setups running in production environments.

Your internal user lists and department structures are processed entirely in memory during the agent conversation. No recruiting data is cached or stored outside your secure MCP sandbox.

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