How to Use the GitScrum MCP in AutoGen

Q: How do I register GitScrum tools with AutoGen agents?

Use mcpservertools with your Vinkius server URL to fetch the tool definitions. Pass this tool list to your AssistantAgent constructor to give them access to the board endpoints.

Build AutoGen multi-agent teams that debate and coordinate GitScrum tasks, projects, and workflows autonomously.

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Create your Vinkius account to connect GitScrum 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 GitScrum with AutoGen

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Consensus-driven project initialization

The GitScrum MCP Server allows AutoGen agents to coordinate project setups using `create_project` and `create_workspace`. A PM agent drafts the scope, while a QA agent reviews it before executing the tool. This collaborative loop ensures that new boards conform to your team standards. The agents debate the project structure until they reach a consensus, then invoke the creation tools.

Multi-agent task triage and MCP board allocation

This integration lets your AutoGen team analyze backlog items using `list_tasks` and `get_task`. A coordinator agent fetches the tasks, a developer agent estimates complexity, and a manager agent assigns them. By splitting the work, the system avoids bottlenecking a single LLM context window. The agents communicate back and forth to balance the workload across your project boards.

Automated board health auditing with AutoGen

Use `project_stats` and `workspace_stats` to trigger automated team debates on sprint progress. Your AutoGen agents analyze these metrics to identify stalled cards or empty columns. If the team detects a bottleneck, they negotiate the best way to reassign tasks. They use `list_project_members` to find available developers and update the board status accordingly.

Setup guide

Set up GitScrum 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 GitScrum 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="GitScrum_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

Get your connection token →

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="GitScrum_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

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

Use `mcp_server_tools` with your Vinkius server URL to fetch the tool definitions. Pass this tool list to your `AssistantAgent` constructor to give them access to the board endpoints.

Yes, agents can share the toolset to collaborate on tasks. One agent can call `list_tasks` to gather data, while another uses `get_task` to inspect specific issues.

AutoGen coordinates calls sequentially through its conversational loop, which naturally paces requests. This prevents your agents from spamming endpoints like `workspace_stats` during active debates.

Yes, the framework supports both transports. You can configure the `StreamableHttpServerParams` to point to your managed Vinkius endpoint over HTTP.

The MCP Server handles authentication securely through a single token managed by Vinkius. Tools like `get_me` and `my_role` run within an isolated sandbox, keeping your credentials hidden from the conversing agents.

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