How to Use the Craft.io MCP in Pydantic AI

Q: How do I configure Craft.io for Pydantic AI?

Install the slim package and define an MCPToolset pointing to the server URL. Pass this set into your agent to enable type-safe tool execution.

Q: Can Pydantic AI handle Craft.io lists?

Yes, listitems returns a typed collection. Your agent iterates through these items using your defined schema, preventing runtime errors.

Enforce strict types in Pydantic AI when connecting to Craft.io.

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Connect Craft.io MCP to Pydantic AI

Create your Vinkius account to connect Craft.io 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 Craft.io with Pydantic AI

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Strictly typed responses for Pydantic AI

Every call to `get_item` or `list_workspaces` is validated against your Pydantic models. If the server returns malformed data, your agent stops immediately. This prevents corrupted state from entering your product logic. You get reliable data structures every time you query your workspace.

Manage product items in Pydantic AI

Your agent uses `create_item` to push updates back to your workspace. The response is parsed into your schema, ensuring your local agent state matches the remote record. This bidirectional sync happens with full type safety. You can trust the data flowing in and out of your agent.

Fetch portfolio financials for Pydantic AI

The `get_company_financials` tool returns structured data that your agent can process safely. It maps complex API responses into simple Python objects for your app. This allows for complex analysis without manual parsing code. Your agent works with clean, validated input.

Setup guide

Set up Craft.io 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": {
        "craftio-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Craft.io transactions")
print(result.output)

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Common questions about Craft.io MCP in Pydantic AI

It guarantees that the data your agent sees matches your expected format. If the API changes, your agent crashes safely instead of hallucinating values.

Install the slim package and define an `MCPToolset` pointing to the server URL. Pass this set into your agent to enable type-safe tool execution.

Your roadmap items are validated on the fly. The connection is ephemeral, ensuring that no sensitive product strategy data persists on Vinkius infrastructure.

Yes, `list_items` returns a typed collection. Your agent iterates through these items using your defined schema, preventing runtime errors.

Yes, it supports both Streamable HTTP and SSE transports. You select the transport that fits your local development environment.

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