Replicate 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 Replicate 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
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="replicate_agent",
tools=tools,
system_message=(
"You help users with Replicate. "
"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 Replicate MCP Server
Connect your conversational assistant directly to the Replicate ecosystem. This integration grants your AI the ability to interact programmatically with a vast library of open-source machine learning models without running them on your local hardware. From orchestrating complex image generations to spinning up specialized language models, you can command AI workflows directly from your chat.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Replicate tools. Connect 12 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
- Execute Predictions — Command the assistant to execute specific model versions on your behalf (
create_prediction) by supplying a payload of variables. Monitor long-running processes by retrieving outputs and execution status reliably (get_prediction) or cancel them at will (cancel_prediction). - Discover Models — Instruct the AI to intelligently scan the Replicate platform for models matching a specific use case using
search_models. You can also explore trending and categorized models by leveraging thelist_collectionsaction. - Analyze Model Metadata — Whenever you discover a new model, query its precise owner and name (
get_model) to extract the exact schema and parameter requirements necessary for a successful execution. You can also view a log of your own executed tasks (list_predictions).
The Replicate 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 Replicate to AutoGen via MCP
Follow these steps to integrate the Replicate 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 Replicate automatically
Why Use AutoGen with the Replicate MCP Server
AutoGen provides unique advantages when paired with Replicate through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Replicate tools to solve complex tasks
Role-based architecture lets you assign Replicate 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 Replicate tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Replicate tool responses in an isolated environment
Replicate + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Replicate MCP Server delivers measurable value.
Collaborative analysis: one agent queries Replicate while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Replicate, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Replicate data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Replicate responses in a sandboxed execution environment
Replicate MCP Tools for AutoGen (12)
These 12 tools become available when you connect Replicate to AutoGen via MCP:
cancel_prediction
Cancels a prediction that is currently running
create_prediction
g., image generation, LLMs). Provide the model version ID and inputs as a JSON object. Starts a new model prediction on Replicate
get_account
Retrieves the authenticated Replicate account details
get_collection
Provide the collection slug (e.g., "text-to-image"). Retrieves a specific collection of models by its slug
get_model
Retrieves details for a specific model
get_prediction
). Retrieves the status and output of a prediction
list_collections
g., "Image-to-Text", "Audio Generation"). Lists curated collections of models
list_deployments
Lists your active model deployments on Replicate
list_hardware
Lists available GPU hardware options for running models
list_models
Lists public models available on Replicate
list_predictions
Lists recent predictions made by the user
search_models
Searches for public models on Replicate
Example Prompts for Replicate in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Replicate immediately.
"List my recent predictions."
"Query Replicate to search for 'TTS' models."
"Cancel the prediction that has the ID `p_abc123`."
Troubleshooting Replicate MCP Server with AutoGen
Common issues when connecting Replicate to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Replicate + AutoGen FAQ
Common questions about integrating Replicate 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 Replicate with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
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 Replicate to AutoGen
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.