Scale AI MCP Server for AutoGenGive AutoGen instant access to 11 tools to Cancel Task, Create Batch, Create Image Annotation Task, and more
GDPR Free for SubscribersMicrosoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Scale AI 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 Scale AI MCP Server for AutoGen is a standout in the Ai Frontier category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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="scale_ai_agent",
tools=tools,
system_message=(
"You help users with Scale AI. "
"11 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 Scale AI MCP Server
Connect your Scale AI account to any AI agent to orchestrate large-scale data labeling and fine-tuning pipelines through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Scale AI tools. Connect 11 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
- Project Management — Create and configure projects for specific labeling types like image annotation or semantic segmentation.
- Batch Operations — Organize high-volume work into batches and finalize them to trigger the labeling process.
- Multi-Modal Tasks — Submit tasks for Image Annotation, Semantic Segmentation, and Video Playback directly via API.
- Task Lifecycle — Retrieve detailed status of individual tasks or cancel pending ones to manage your budget and throughput.
- Parameter Tuning — Update project-level instructions and parameters dynamically to refine labeling quality.
The Scale AI MCP Server exposes 11 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 11 Scale AI tools available for AutoGen
When AutoGen connects to Scale AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning data-labeling, rlhf, machine-learning, 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.
Cancel task on Scale AI
Optionally clears the unique_id to reuse it. Cancel a pending task
Create batch on Scale AI
Create a new batch
Create image annotation task on Scale AI
Create an Image Annotation task
Create named entity recognition task on Scale AI
Create a Named Entity Recognition task
Create project on Scale AI
Create a new Scale project
Create segment annotation task on Scale AI
Create a Semantic Segmentation task
Create text collection task on Scale AI
Create a Text Collection task
Create video playback annotation task on Scale AI
Create a Video Annotation task
Finalize batch on Scale AI
Finalize a batch
Get task on Scale AI
Retrieve a specific task
Update project params on Scale AI
Update project parameters
Connect Scale AI to AutoGen via MCP
Follow these steps to wire Scale AI 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 Scale AI MCP Server
AutoGen provides unique advantages when paired with Scale AI through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Scale AI tools to solve complex tasks
Role-based architecture lets you assign Scale AI 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 Scale AI tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Scale AI tool responses in an isolated environment
Scale AI + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Scale AI MCP Server delivers measurable value.
Collaborative analysis: one agent queries Scale AI while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Scale AI, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Scale AI data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Scale AI responses in a sandboxed execution environment
Example Prompts for Scale AI in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Scale AI immediately.
"Create a new image annotation project called 'Lidar-Obstacles' for imageannotation."
"Submit an image annotation task to project 'Lidar-Obstacles' with the image URL 'https://example.com/car.jpg'."
"Finalize the batch named 'sprint-01-batch'."
Troubleshooting Scale AI MCP Server with AutoGen
Common issues when connecting Scale AI to AutoGen through Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Scale AI + AutoGen FAQ
Common questions about integrating Scale AI 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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