How to Use the CNMC (Comisión Mercados y Competencia) MCP in Pydantic AI

Validate Spanish market data in Pydantic AI with strict type safety.

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Connect CNMC (Comisión Mercados y Competencia) MCP to Pydantic AI

Create your Vinkius account to connect CNMC (Comisión Mercados y Competencia) 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 CNMC (Comisión Mercados y Competencia) with Pydantic AI

Ask AI about this MCP

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Claude

Perplexity

Type-safe search for Pydantic AI

Use `package_search` to find data catalog IDs. Your agent validates every response against Pydantic models to catch errors early. If the CNMC catalog schema changes, your agent fails immediately. You get full control over the data structures entering your code.

Validated records for Pydantic AI

Call `datastore_search` to import market records. Every row is checked against your defined types before the agent touches it. This prevents silent bugs. You know exactly what data the agent sees before it makes any decisions.

Reliable market analysis in Pydantic AI

Connect this MCP server to your agent framework for robust data handling. You get strict runtime validation for every query. Your logic stays clean. The agent only works with data that matches your expected schema, every single time.

Setup guide

Set up CNMC (Comisión Mercados y Competencia) 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": {
        "cnmc-comision-mercados-y-competencia-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent CNMC (Comisión Mercados y Competencia) transactions")
print(result.output)

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Common questions about CNMC (Comisión Mercados y Competencia) MCP in Pydantic AI

The MCP toolset returns data that your defined Pydantic models must match. If the data structure is invalid, the agent triggers a validation error.

Absolutely. You define the schema for the search results, ensuring your agent only interacts with correctly formatted catalog data.

Yes. Since the agent fails on validation errors, you can catch them in your logic and handle them without crashing your production system.

Yes. You define the models, and the MCP tools provide the data to fill them. It is built for custom, type-safe agent workflows.

The server acts as a read-only interface. It only touches public market records, and your local validation models ensure no unexpected data enters your environment.

Use it with your favorite AI tools

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

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