How to Use the Namely MCP in AutoGen

Enable debate-driven HR automation by connecting Namely to your AutoGen multi-agent system.

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Connect Namely MCP to AutoGen

Create your Vinkius account to connect Namely 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 Namely with AutoGen

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Negotiate Namely data in AutoGen

Let your agents debate the best course of action using Namely data. One agent might pull `list_groups` to define a project team, while another challenges the selection based on availability. This consensus-driven approach prevents errors. By having multiple agents cross-reference Namely records, your system arrives at decisions that are verified by different perspectives.

Coordinate Namely tools in AutoGen

Assign specific roles to your agents. A researcher agent calls `get_profile` to gather details, while a coordinator agent uses `list_jobs` to verify roles across the organization. Your agents work in concert. They discuss the data they receive, ensuring that every action taken with Namely is intentional and aligned with your system's goals.

Automate Namely decisions in AutoGen

Build systems that handle complex HR requests through deliberation. When a user asks for a team report, your agents negotiate which `list_reports` or `list_teams` call provides the best answer. You avoid single-point-of-failure logic. The agents check each other's work, using Namely data as the source of truth for all organizational decisions.

Setup guide

Set up Namely 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 Namely 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="Namely_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Get your connection token →

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Common questions about Namely MCP in AutoGen

Agents call Namely tools to retrieve data, then debate the significance of that data. The AutoGen framework manages the conversation between agents as they access Namely.

Yes. Every agent in your group can access the Namely tool set. They negotiate who has the authority to perform specific queries based on their assigned role.

The tool adapter automatically maps the Namely schema for your agents. You don't need to manually update the agent definitions when the Namely API evolves.

You define permissions at the server level. Only the agents you authorize will have the ability to invoke Namely tools during their debates.

Your Namely data is isolated within the ephemeral sandbox. Even during agent debates, sensitive HR information is only exchanged as needed to reach a resolution.

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