How to Use the Filemail MCP in Pydantic AI

Q: How does Pydantic AI validate Filemail transfer configurations?

The framework maps responses from getconfiguration to strict Python models. If Filemail returns unexpected fields, the toolset raises a validation error before your agent can act on bad data.

Q: Can I manage Filemail contacts safely using Pydantic AI?

Yes, you can use listcontacts to retrieve recipients. The framework validates each contact's email structure, ensuring your agent never sends files to a broken address.

Q: What happens if a Filemail login fails in Pydantic AI?

The login tool returns a structured error model if authentication fails. Pydantic AI catches this immediately, preventing the agent from trying to call initializetransfer with invalid credentials.

Q: How do I check my inbox programmatically?

You use the listreceivedtransfers tool to pull incoming packages. Your agent can loop through this list to download or catalog new files automatically.

Run type-safe Filemail transfers using Pydantic AI to validate file metadata and transfer configurations at runtime.

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Connect Filemail MCP to Pydantic AI

Create your Vinkius account to connect Filemail 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 Filemail with Pydantic AI

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Type-safe transfers with Pydantic AI MCP Server

The `initialize_transfer` tool enforces strict schema validation on your Filemail metadata. This MCP server ensures no data leaves your system without proper formatting, matching Pydantic AI models perfectly. This prevents runtime failures during long-running Filemail transfers. If an email address is malformed, the Pydantic AI framework raises a validation error immediately, saving bandwidth and time.

Validate account configurations and user profiles

The `get_configuration` tool returns your branded Filemail portal settings and transfer limits directly into type-safe Pydantic AI models. Your agent uses `get_user` to check active subscription tiers before starting a transfer. By validating these configurations at runtime, you avoid silent failures in your Filemail pipelines. The MCP toolset makes sure your Pydantic AI code fails loudly and safely when issues arise.

Query and clean transfer histories

The `list_sent_transfers` tool fetches your outgoing Filemail history, parsing each record into a structured Pydantic AI schema. Your agent can run `get_transfer_details` to verify download logs without risk of corrupted data. For automated cleanup, `delete_transfer` removes old Filemail packages based on strict validation rules defined in your Pydantic AI schema. This keeps your storage usage optimized without manual oversight.

Setup guide

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

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

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

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Common questions about Filemail MCP in Pydantic AI

The framework maps responses from `get_configuration` to strict Python models. If Filemail returns unexpected fields, the toolset raises a validation error before your agent can act on bad data.

Yes, you can use `list_contacts` to retrieve recipients. The framework validates each contact's email structure, ensuring your agent never sends files to a broken address.

The `login` tool returns a structured error model if authentication fails. Pydantic AI catches this immediately, preventing the agent from trying to call `initialize_transfer` with invalid credentials.

You use the `list_received_transfers` tool to pull incoming packages. Your agent can loop through this list to download or catalog new files automatically.

Your passwords, file metadata, and contact lists are processed entirely in memory within a secure, ephemeral V8 sandbox on the MCP server. No data is cached or written to persistent storage, guaranteeing complete privacy for your transfers.

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