Flow MCP Server for AutoGen 12 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Flow as an MCP tool provider through the Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="flow_agent",
tools=tools,
system_message=(
"You help users with Flow. "
"12 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Flow MCP Server
Connect your Flow account to any AI agent and automate your project management and team collaboration through the Model Context Protocol (MCP). Flow (getflow.com) provides a clean and powerful platform for organizing work, tracking task progress, and facilitating team discussions. Now, you can manage your workspaces, projects, and individual tasks directly through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Flow tools. Connect 12 tools through the Vinkius and assign role-based access — a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Project Coordination — List all projects within your workspaces and retrieve detailed metadata, including ownership and due dates.
- Task Management — Create, update, and list tasks across workspaces, projects, or specific task lists. Change statuses (incomplete/completed) instantly.
- Organized Lists — Access and list task groups (Lists) within projects to maintain a clear hierarchy of work.
- Team Interaction — List all workspace members and teams, and participate in task discussions by reading or adding comments.
- Workspace Oversight — Get a high-level view of all the top-level workspaces you belong to.
- Real-time Updates — Fetch specific task details or metadata to keep your team informed and your projects on track.
The Flow MCP Server exposes 12 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Flow to AutoGen via MCP
Follow these steps to integrate the Flow MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 12 tools from Flow automatically
Why Use AutoGen with the Flow MCP Server
AutoGen provides unique advantages when paired with Flow through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Flow tools to solve complex tasks
Role-based architecture lets you assign Flow tool access to specific agents — a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Flow tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Flow tool responses in an isolated environment
Flow + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Flow MCP Server delivers measurable value.
Collaborative analysis: one agent queries Flow while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Flow, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Flow data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Flow responses in a sandboxed execution environment
Flow MCP Tools for AutoGen (12)
These 12 tools become available when you connect Flow to AutoGen via MCP:
add_task_comment
Post a comment
create_task
Create a new task
get_project
Get project details
get_task
Get task details
list_projects
List projects in workspace
list_task_comments
List task discussions
list_task_lists
List lists in project
list_tasks
List tasks
list_workspace_members
List team members
list_workspace_teams
List workspace teams
list_workspaces
List top-level workspaces
update_task
). Update an existing task
Example Prompts for Flow in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Flow immediately.
"List all my Flow projects in the 'Marketing' workspace."
"Create a new task: 'Review final design mockup' in the 'Design' list."
"Add a comment to task 'task_123': 'Design looks great, proceed to coding'."
Troubleshooting Flow MCP Server with AutoGen
Common issues when connecting Flow to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Flow + AutoGen FAQ
Common questions about integrating Flow MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Flow with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Flow to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.
