How to Use the Claid AI MCP in Pydantic AI

Q: What's the setup for using Claid AI with Pydantic AI?

It's one line. You create an MCPToolset instance with your Vinkius server URL and pass it to your agent's toolsets list. Pydantic AI handles the tool discovery and response validation from there.

Get type-safe, validated image edits from Claid AI in any Python application using Pydantic AI.

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Connect Claid AI MCP to Pydantic AI

Create your Vinkius account to connect Claid AI to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Claid AI with Pydantic AI

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Get Guaranteed-Correct Image Edits

This MCP Server gives your Pydantic AI agent tools for reliable image processing. Use `enhance_image` to run multiple edits in one go, like upscaling and background removal. The response is automatically validated against a Pydantic model. If the Claid API ever returns an unexpected field or a malformed response, your agent will raise a `ValidationError` immediately. No silent data corruption. You get exactly what your model expects, or you get a loud, clear error.

A Type-Safe Way to Manage Claid AI

Go beyond just editing images. The `get_claid_account_info` tool returns your account status, and Pydantic AI ensures the response object has the `quota` and `balance` fields you expect. It makes building reliable, self-monitoring agents much simpler. The same principle applies to managing async tasks. When your agent calls `get_processing_task_details`, the result is parsed into a strict model. You know for a fact whether the task is pending, complete, or failed.

Discover Operations with Runtime Validation

Let your agent discover what it can do safely. The `list_available_ai_operations` tool returns a list of possible edits. Pydantic AI will validate that the response is a clean list of strings, as expected. You can apply the same safety to `list_claid_collections` and `list_claid_webhooks`. Your agent gets structured, validated data about the environment it's working in, which is critical for writing correct, predictable code.

Setup guide

Set up Claid AI MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "claid-ai-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Claid AI tools.",
)

result = await agent.run("List recent Claid AI transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Claid AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about Claid AI MCP in Pydantic AI

When you connect the Claid AI MCP Server, Pydantic AI automatically validates every API response against a corresponding model. If the data from a tool like `get_claid_account_info` doesn't match the schema, it raises an error instead of letting your agent proceed with bad data.

It's one line. You create an `MCPToolset` instance with your Vinkius server URL and pass it to your agent's `toolsets` list. Pydantic AI handles the tool discovery and response validation from there.

Yes. Pydantic AI is model-agnostic, so you can use OpenAI, Anthropic, Gemini, or a local model. The Claid AI tools will work the same way regardless of the underlying LLM your agent uses.

No, it’s for managing the whole workflow. Your agent can use `get_claid_account_info` to check your quota and `get_processing_task_details` to monitor jobs, all with the safety of Pydantic validation. This MCP connection is more than just a simple image filter.

The Claid AI server only gets the image data you explicitly send for a given operation. Vinkius isolates that operation in an ephemeral container that's destroyed afterward. Your account information is also only fetched on demand and is never stored by the MCP server.

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