How to Use the Digify MCP in Pydantic AI

Validate your Digify document workflows with Pydantic AI for type-safe, error-free secure file management.

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Connect Digify MCP to Pydantic AI

Create your Vinkius account to connect Digify 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 Digify with Pydantic AI

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Perplexity

Type-safe Digify tools for Pydantic AI

Every response from `get_file_access_statistics` is validated against your Pydantic models. You get runtime guarantees that your agent's data is accurate. This prevents silent failures when the API returns unexpected field types. You can trust the data your agent uses to track file viewership.

Strict document auditing

Run `quick_file_audit` to get a summary of security rights. If the structure doesn't match your schema, the agent will throw an immediate validation error. This keeps your agent's decision-making process clean and predictable. You avoid the risks of hallucinated fields or corrupted audit logs.

Controlled secure file management

Use `list_secure_files` to catalog your repository. The Pydantic AI framework ensures every file object strictly follows your defined structure. This provides a rigid foundation for your agent's operations. You gain total control over how your application handles document metadata.

Setup guide

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

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

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

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Common questions about Digify MCP in Pydantic AI

It does. If an API request fails, the MCP server maps the error to a standard code, and your agent handles the exception immediately.

Install the MCP toolset and pass it to your agent constructor. Your agent will automatically generate Pydantic models for every tool it discovers.

You can. If you only need a subset of the ten available tools, you can restrict the exposed set during agent initialization.

The tool will return an empty result or a specific error code that your agent can catch. Pydantic AI will validate that the result matches your expected output schema.

Access is restricted to the specific endpoints defined in the MCP schema. Your environment manages the authentication token, ensuring only your agent accesses the file metadata.

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