Together AI MCP Server for Pydantic AI 7 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Together AI through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Together AI "
"(7 tools)."
),
)
result = await agent.run(
"What tools are available in Together AI?"
)
print(result.data)
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.
Pydantic AI validates every Together AI tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the Together AI MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 7 tools from Together AI with type-safe schemas
Why Use Pydantic AI with the Together AI MCP Server
Pydantic AI provides unique advantages when paired with Together AI through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your Together AI integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Together AI connection logic from agent behavior for testable, maintainable code
Together AI + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Together AI MCP Server delivers measurable value.
Type-safe data pipelines: query Together AI with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Together AI tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Together AI and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Together AI responses and write comprehensive agent tests
Together AI MCP Tools for Pydantic AI (7)
These 7 tools become available when you connect Together AI to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Together AI to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiTogether AI + Pydantic AI FAQ
Common questions about integrating Together AI MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
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 Pydantic AI
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.