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Simian MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Add Project Comment, Create Reel, Delete Media, and more

Built by Vinkius GDPR 12 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Simian through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Ask AI about this App Connector for Pydantic AI

The Simian app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python
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 Simian "
            "(12 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Simian?"
    )
    print(result.data)

asyncio.run(main())
Simian
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Simian MCP Server

The Simian MCP server enables your AI agent to manage your creative workflows. Retrieve media links, orchestrate review processes, and analyze viewer engagement directly from the chat interface.

Pydantic AI validates every Simian tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through 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.

The Simian MCP Server exposes 12 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.

All 12 Simian tools available for Pydantic AI

When Pydantic AI connects to Simian through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-sharing, creative-workflow, media-review, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

add_project_comment

Add a new comment or approval status to a file

create_reel

Create a new reel

delete_media

Permanently remove a file from the library

get_account_info

Retrieve account details and usage statistics

get_media

Get metadata for a specific media file

get_project_comments

Retrieve comments and annotations for a project file

get_reel

Get details of a specific reel

list_media

List all media files in the library

list_projects

List all active review and approval projects

list_reels

List all created reels (presentations)

share_reel

Send a reel to recipients via email or short link

update_media

Update metadata for a media file

Connect Simian to Pydantic AI via MCP

Follow these steps to wire Simian into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 12 tools from Simian with type-safe schemas

Why Use Pydantic AI with the Simian MCP Server

Pydantic AI provides unique advantages when paired with Simian through the Model Context Protocol.

01

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

02

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Simian integration code

03

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

04

Dependency injection system cleanly separates your Simian connection logic from agent behavior for testable, maintainable code

Simian + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Simian MCP Server delivers measurable value.

01

Type-safe data pipelines: query Simian with guaranteed response schemas, feeding validated data into downstream processing

02

API orchestration: chain multiple Simian tool calls with Pydantic validation at each step to ensure data integrity end-to-end

03

Production monitoring: build validated alert agents that query Simian and output structured, schema-compliant notifications

04

Testing and QA: use Pydantic AI's dependency injection to mock Simian responses and write comprehensive agent tests

Example Prompts for Simian in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Simian immediately.

01

"Get the review link for project 'Summer Campaign'."

02

"Summarize the analytics for my latest reel."

03

"Invite 'client@brand.com' to review project 104."

Troubleshooting Simian MCP Server with Pydantic AI

Common issues when connecting Simian to Pydantic AI through the Vinkius, and how to resolve them.

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Simian + Pydantic AI FAQ

Common questions about integrating Simian MCP Server with Pydantic AI.

01

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
02

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
03

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Simian MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.