Roboflow MCP Server for AutoGenGive AutoGen instant access to 29 tools to Add Projects To Folder, Auto Label, Cancel Training, and more
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Roboflow as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
Ask AI about this MCP Server for AutoGen
The Roboflow MCP Server for AutoGen is a standout in the Developer Tools category — giving your AI agent 29 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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="roboflow_agent",
tools=tools,
system_message=(
"You help users with Roboflow. "
"29 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 Roboflow MCP Server
Connect Roboflow to your AI agent to streamline your computer vision pipeline. From dataset management to model training and inference, handle your entire CV lifecycle through natural language.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Roboflow tools. Connect 29 tools through 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
- Workspace & Project Management — List projects, create new ones, or fork from Roboflow Universe to jumpstart your development.
- Dataset Operations — Upload images (via URL or Base64), manage versions, and download datasets in various formats like COCO or YOLO.
- Model Training — Start training runs, monitor results, and retrieve precise performance metrics (mAP, precision, recall) for any version.
- Image Search — Search and filter images within your workspace to audit your data and improve model accuracy.
- Inference & Results — Run inference on images and retrieve results to verify model behavior in real-time.
The Roboflow MCP Server exposes 29 tools through the Vinkius. Connect it to AutoGen in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 29 Roboflow tools available for AutoGen
When AutoGen connects to Roboflow through Vinkius, your AI agent gets direct access to every tool listed below — spanning computer-vision, dataset-management, model-training, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Add projects to folder on Roboflow
Add projects to a folder (Enterprise)
Auto label on Roboflow
Start an auto-labeling job using foundation models
Cancel training on Roboflow
Cancel an active training job
Create annotation job on Roboflow
Assign a batch of images to a labeler and reviewer
Create folder on Roboflow
Create a project folder (Enterprise)
Create project on Roboflow
Create a new project in a workspace
Delete images on Roboflow
Delete multiple images from a project
Delete project on Roboflow
Delete a project or version (moves to Trash)
Download dataset on Roboflow
Retrieve a download link for a zipped dataset in a specific format
Fork universe project on Roboflow
Fork a public project from Roboflow Universe
Get async task on Roboflow
Track long-running operations like forking or large exports
Get dataset health on Roboflow
Check dataset health (class distribution, missing annotations, etc)
Get image on Roboflow
Get details for a specific image
Get project on Roboflow
Get project details, metadata, and versions
Get root on Roboflow
Verify authentication and retrieve default workspace
Get training results on Roboflow
Retrieve metrics and status for a version training run
Get version on Roboflow
Retrieve metadata for a specific dataset version
List folders on Roboflow
List project folders in a workspace (Enterprise)
List trash on Roboflow
List items in the workspace trash
List workspace projects on Roboflow
List information about a workspace and its projects
Manage image tags on Roboflow
Add, remove, or set tags on an image
Restore trash on Roboflow
Restore an item from the trash
Run inference on Roboflow
Run inference on an image using hosted models
Search project images on Roboflow
Search and filter images within a specific project
Search workspace images on Roboflow
Search and filter images within a workspace
Start training on Roboflow
Start training a model on a dataset version
Stop training on Roboflow
Early stop an active training job
Upload annotation on Roboflow
Attach an annotation file to an existing image
Upload image on Roboflow
Upload an image to a project
Connect Roboflow to AutoGen via MCP
Follow these steps to wire Roboflow into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.
Install AutoGen
pip install "autogen-ext[mcp]"Replace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenIntegrate into workflow
Explore tools
Why Use AutoGen with the Roboflow MCP Server
AutoGen provides unique advantages when paired with Roboflow through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Roboflow tools to solve complex tasks
Role-based architecture lets you assign Roboflow 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 Roboflow tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Roboflow tool responses in an isolated environment
Roboflow + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Roboflow MCP Server delivers measurable value.
Collaborative analysis: one agent queries Roboflow while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Roboflow, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Roboflow data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Roboflow responses in a sandboxed execution environment
Example Prompts for Roboflow in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Roboflow immediately.
"List all projects in my Roboflow workspace 'industrial-safety'."
"Upload this image URL to the 'Hard Hat Detection' project in workspace 'industrial-safety'."
"Show me the training metrics for version 5 of the 'Forklift Tracking' project."
Troubleshooting Roboflow MCP Server with AutoGen
Common issues when connecting Roboflow to AutoGen through Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Roboflow + AutoGen FAQ
Common questions about integrating Roboflow 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?
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