How to Use the Greenhouse Alternative MCP in AutoGen

Q: How do I handle destructive operations with Greenhouse Alternative in AutoGen?

You should assign tools like deleteapplication only to a highly restricted agent. Require a human-in-the-loop proxy agent in AutoGen to approve the deletion before the tool call is sent to the MCP server.

Build multi-agent recruiting teams that debate and manage your Greenhouse Alternative pipeline inside AutoGen.

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Connect Greenhouse Alternative MCP to AutoGen

Create your Vinkius account to connect Greenhouse Alternative 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 Greenhouse Alternative with AutoGen

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Run consensus-driven candidate screening in AutoGen

This Greenhouse Alternative MCP server allows AutoGen agents to collaborate on candidate reviews. You can set up a screening agent to fetch profiles with `get_application` and a compliance agent to review audit logs via `get_audit_log_events` before moving candidates forward. These agents debate the merits of each applicant in a shared conversation. Only when both agents agree does the system execute `update_application` to advance the candidate to the next interview stage.

Coordinate job board distribution across agents

This toolset lets you deploy dedicated AutoGen agents to manage your job boards. One agent can monitor active postings using `list_board_jobs` while another tracks applicant volume via `list_applications` to identify slow-hiring departments. When a department needs more candidates, the agents negotiate where to publish tracking links using `create_partner_tracking_link`. The entire process—from identifying the gap to generating the link—happens through structured agent conversations.

Secure candidate ingestion with multi-agent validation

This server enables safe, multi-agent validation of incoming job board submissions. When a new application arrives, a parser agent processes it using `submit_board_application` while a security agent checks candidate details via `get_candidate_activity_feed`. If the security agent flags an anomaly, it blocks the ingestion pipeline. The coordinator agent can then decide whether to safely run `delete_application` or route the candidate to a human recruiter for manual review.

Setup guide

Set up Greenhouse Alternative 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 Greenhouse Alternative 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="Greenhouse Alternative_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Common questions about Greenhouse Alternative MCP in AutoGen

You register the MCP server tools with your AutoGen agent group. One agent can query candidate details via `get_application`, while a coordinator agent uses that data to run `add_application_to_candidate` based on the group's consensus.

You should assign tools like `delete_application` only to a highly restricted agent. Require a human-in-the-loop proxy agent in AutoGen to approve the deletion before the tool call is sent to the MCP server.

Yes, you can set up a sourcing agent to list partner jobs using `list_partner_jobs` and a submission agent to run `submit_partner_candidate`. The agents will converse to match candidates with open roles before submitting them.

AutoGen supports both stdio and HTTP transports. For cloud deployments, use the Streamable HTTP transport configured with your secure Vinkius endpoint to access the recruiting tools safely.

Every transaction executed by your AutoGen agents is recorded. You can track all agent-initiated modifications by querying `get_audit_log_events`, ensuring full accountability for every automated candidate update.

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