How to Use the Fastn MCP in Pydantic AI

Q: Can I use Fastn to manage credentials in Pydantic AI?

You can use getcredentials to retrieve secrets at runtime. Because Pydantic AI handles the types, you know exactly what format to expect for your connection strings.

Q: How secure is my data in the Fastn MCP Server?

Your credentials are encrypted using storecredentials. The server acts as a secure boundary, ensuring your keys never touch your agent's execution memory in an unvalidated state.

Use Pydantic AI with Fastn to ensure every workflow execution matches your strict data requirements.

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Connect Fastn MCP to Pydantic AI

Create your Vinkius account to connect Fastn 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 Fastn with Pydantic AI

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Type-safe workflow execution with Fastn

Pydantic AI validates every response from `execute_flow` against your models. If the Fastn output doesn't match your schema, the agent stops immediately rather than proceeding with bad data. This prevents silent errors in your automation. You get a clear validation error the moment something isn't right, saving you from debugging corrupt state later.

Audit your Fastn workflow history

Retrieving execution history is straightforward with `list_executions`. Because you're using Pydantic models, the data returned is always structured exactly as you expect. Use `get_execution` to pull specific traces for deeper inspection. It’s the best way to verify that your agent's previous logic followed the intended path.

Maintain Fastn definitions with confidence

Managing your workflow catalog is safer when you use `publish_workflow` through a type-safe interface. You can be certain your deployment parameters are correct before they hit the server. `get_workflow` lets your agent inspect existing definitions before making changes. It ensures you don't overwrite critical logic with incorrect configuration data.

Setup guide

Set up Fastn 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": {
        "fastn-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Fastn MCP in Pydantic AI

Every MCP response is automatically checked against your defined Pydantic models. If the server returns something unexpected, the agent raises a validation error immediately.

Yes, you use the MCPToolset to connect. It provides a clean, typed interface for all 16 tools, ensuring your agent behaves predictably.

You can use `get_credentials` to retrieve secrets at runtime. Because Pydantic AI handles the types, you know exactly what format to expect for your connection strings.

The agent will receive a clear failure message. You can then use `get_execution` to pull the trace and see exactly where the logic diverged from your expectations.

Your credentials are encrypted using `store_credentials`. The server acts as a secure boundary, ensuring your keys never touch your agent's execution memory in an unvalidated state.

Use it with your favorite AI tools

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