How to Use the Basecamp MCP in AutoGen

Q: How do AutoGen agents coordinate on Basecamp tasks?

Your agents use a shared group chat. One agent calls listtodos to find pending work, another analyzes the priorities, and a third calls updatetodo to assign the task.

Q: Can AutoGen agents create Basecamp projects autonomously?

Yes, if you grant them permission. An agent can trigger createproject once the group chat agrees that a new initiative has started.

Q: Does AutoGen expose my Basecamp user profile data?

Your profile details retrieved via getmyprofile are strictly scoped to the active session. Vinkius runs the MCP Server in a zero-trust environment, keeping your personal credentials and account details safe.

Let your AutoGen agents debate, coordinate, and execute tasks directly inside your Basecamp workspace.

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Connect Basecamp MCP to AutoGen

Create your Vinkius account to connect Basecamp 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 Basecamp with AutoGen

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Multi-Agent Debate on Basecamp Project Setup

The `create_project` tool initializes a new workspace, but your AutoGen agents debate the configuration first. A PM agent proposes the project structure, while an ops agent reviews it before execution. Once they agree, the executing agent calls the tool and uses `update_project` to apply the finalized settings, ensuring your workspace matches team standards.

Collaborative Task Management via AutoGen MCP Server

The `create_todo` tool adds tasks to your list, but only after your AutoGen agents reach consensus on who should do the work. One agent checks team workload using `list_project_people` while another suggests assignees. If a task is completed, an agent calls `complete_todo`. If another agent flags a quality issue, it can call `uncomplete_todo` to reopen the task for further discussion.

Automated Code Review and Commenting

The `create_comment` tool lets your agents post feedback directly to Basecamp recordings. A QA agent and a developer agent can debate a bug fix in their own chat, then post the consensus report as a rich-text comment. To keep the context accurate, they use `get_message` to pull the original discussion. This ensures the posted comment addresses the exact problem your team is facing.

Setup guide

Set up Basecamp 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 Basecamp 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="Basecamp_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Basecamp. 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 Basecamp MCP in AutoGen

Your agents use a shared group chat. One agent calls `list_todos` to find pending work, another analyzes the priorities, and a third calls `update_todo` to assign the task.

Yes, if you grant them permission. An agent can trigger `create_project` once the group chat agrees that a new initiative has started.

Use the Vinkius MCP Server adapter. It automatically converts tools like `list_projects` into schemas that your AutoGen AssistantAgent can understand and call.

The agents will continue their internal debate using MCP protocols until they reach consensus. Only then will the designated writer agent call `create_comment` to post the final decision.

Your profile details retrieved via `get_my_profile` are strictly scoped to the active session. Vinkius runs the MCP Server in a zero-trust environment, keeping your personal credentials and account details safe.

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