How to Use the 15Five MCP in AutoGen

Q: How do I register 15Five MCP Server tools with AutoGen agents?

Install autogen-extmcp and use the MCP parameters to fetch the tools. You then pass the tool list directly to your AssistantAgent constructor.

Q: How do AutoGen agents access 15Five department structures?

The agents call listdepartments to view the organizational setup. This lets them negotiate and assign tasks based on specific team structures.

Q: What is the role of the listusers tool in AutoGen?

The listusers tool provides the precise employee identifiers needed for queries. This MCP tool lets agents check individual check-ins or objectives during debates.

Let your AutoGen agents debate team performance, align OKRs, and send peer recognition.

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Connect 15Five MCP to AutoGen

Create your Vinkius account to connect 15Five 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 15Five with AutoGen

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Multi-Agent Performance Review with AutoGen

The `list_checkins` tool allows your AutoGen agents to review employee submissions during automated performance evaluations. One agent can analyze the raw check-ins while another evaluates alignment with company goals. This collaborative debate ensures that performance summaries are balanced and objective. The agents cross-reference the data before presenting their final report.

Consensus-Based Recognition via MCP Server Tools

The `send_high_five` tool is executed only after your AutoGen agents agree that a milestone warrants public recognition. An evaluation agent flags a completed objective, and a peer agent approves the draft message. By integrating `list_users`, the system ensures the compiled praise goes to the correct email address. This multi-agent check prevents accidental or duplicate postings.

Align Team Goals Across Departments

The `list_objectives` tool supplies company OKRs directly to your AutoGen conversation loop. Agents use this data to debate whether current project tasks match official targets. Combining this with `list_departments` allows the agents to analyze goal alignment across different business units. They negotiate resource allocation based on actual department objectives.

Setup guide

Set up 15Five 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 15Five 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="15Five_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent 15Five 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="15Five_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent 15Five 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 15Five. 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 15Five MCP in AutoGen

Install `autogen-ext[mcp]` and use the MCP parameters to fetch the tools. You then pass the tool list directly to your `AssistantAgent` constructor.

Yes, one agent can write the recognition draft while a second agent verifies the details. Once they reach a consensus, the agent triggers `send_high_five` to post it.

The agents call `list_departments` to view the organizational setup. This lets them negotiate and assign tasks based on specific team structures.

The `list_users` tool provides the precise employee identifiers needed for queries. This MCP tool lets agents check individual check-ins or objectives during debates.

Yes, your employee check-ins and OKR details are kept completely private. Vinkius runs the integration in secure, ephemeral V8 isolates, preventing any data leaks during agent interactions.

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