How to Use the Alegra MCP in Pydantic AI

Enforce strict type-safety for Alegra operations using Pydantic AI and this MCP Server.

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Connect Alegra MCP to Pydantic AI

Create your Vinkius account to connect Alegra 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 Alegra with Pydantic AI

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Validate Alegra responses with Pydantic AI

Every call to `get_company_info` is checked against your models. If the server returns malformed data, your agent catches it immediately. This prevents bad accounting data from polluting your logic. Pydantic AI ensures that your agent only acts on verified, expected structures.

Run type-safe Alegra queries in Pydantic AI

Use `list_contacts` to pull your client list. The framework validates every field returned by the tool, ensuring your agent knows exactly who it's talking to. It maps the raw output to your defined classes. You get cleaner code and fewer runtime exceptions when processing customer files.

Execute Alegra transactions with Pydantic AI

Create invoices using `create_invoice` while wrapped in a type-checked flow. The agent validates the input parameters before sending them to your accounting account. This adds a layer of safety to your financial automation. You know exactly what data hits the server, reducing the risk of accidental record corruption.

Setup guide

Set up Alegra 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": {
        "alegra-extended-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Alegra MCP in Pydantic AI

Install the slim MCP package and use the MCPToolset class. Pass the server URL to the toolset and register it with your agent.

It does. The framework enforces your schema on every response from the server, preventing silent corruption if the accounting API returns unexpected keys.

It works perfectly as an external server. You connect via HTTP, and the framework handles the communication and validation layer.

You manage authentication through the Vinkius endpoint token. The framework keeps this secret out of your logs and uses it only to authorize requests.

It interacts with your invoice and contact databases. The server enforces strict validation on these financial inputs to ensure data integrity.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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