Together AI MCP Server for AutoGen 7 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Together AI 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="together_ai_agent",
tools=tools,
system_message=(
"You help users with Together AI. "
"7 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 Together AI MCP Server
Connect your Together AI account to any AI agent and integrate bleeding-edge open-source models seamlessly into your workflow. Harness world-class inference speeds to query Llama, Mixtral, and more, or orchestrate specialized model fine-tuning jobs straight from your chat environment.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Together AI tools. Connect 7 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
- Model Discovery — Explore and list all currently supported models on the Together network, identifying the best engine for any NLP or vision task
- Conversational AI — Run chat completion cycles on advanced models simply by supplying a model ID directly from the chat prompt
- Vector Storage Preparation — Generate instant rich embeddings for input texts, ready to populate your analytical databases
- Creative Media — Instruct external diffusion models to generate images using detailed physical descriptions
- Custom Fine-Tuning — Provision custom training runs by indicating a base framework and dataset file, alongside tracking existing job statuses
The Together AI MCP Server exposes 7 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 Together AI to AutoGen via MCP
Follow these steps to integrate the Together AI 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 7 tools from Together AI automatically
Why Use AutoGen with the Together AI MCP Server
AutoGen provides unique advantages when paired with Together AI through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Together AI tools to solve complex tasks
Role-based architecture lets you assign Together 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 Together AI tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Together AI tool responses in an isolated environment
Together AI + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Together AI MCP Server delivers measurable value.
Collaborative analysis: one agent queries Together AI while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Together AI, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Together AI data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Together AI responses in a sandboxed execution environment
Together AI MCP Tools for AutoGen (7)
These 7 tools become available when you connect Together AI to AutoGen via MCP:
chat_completion
Provide a model ID and a JSON array of messages. Executes a chat completion using Together AI models
create_finetune_job
Provide a base model ID and a training file ID. Creates a new fine-tuning job
generate_embeddings
Provide a model ID and a JSON array of strings. Generates vector embeddings for input texts
generate_image
Provide a model ID and descriptive prompt. Generates an image from a text prompt
list_available_models
Lists all AI models available on Together AI
list_finetune_jobs
Lists all fine-tuning jobs
text_completion
Provide a model ID and a prompt. Executes a base text completion
Example Prompts for Together AI in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Together AI immediately.
"List all the models currently available on Together AI."
"Generate an embedding array using model `togethercomputer/m2-bert-80M-8k-retrieval` for the sentence 'The cat sat on the mat'."
Troubleshooting Together AI MCP Server with AutoGen
Common issues when connecting Together AI to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Together AI + AutoGen FAQ
Common questions about integrating Together 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?
Connect Together AI 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 Together AI to AutoGen
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.