How to Use the Diputación de Alicante MCP in Pydantic AI

Q: How do I connect the Diputación de Alicante server to my Pydantic AI agent?

Install the slim package with pip install "pydantic-ai-slimmcp" and initialize MCPToolset with the Vinkius URL. Pass this toolset directly into the toolsets list of your Pydantic AI Agent.

Q: Does Pydantic AI validate the raw JSON output from the Diputación de Alicante server?

Yes, every response from tools like getmunicipalbudgets is validated against Pydantic schemas at runtime. The agent will raise a validation error if the provincial API returns an unexpected data structure.

Q: Can I use SSE transport with the Diputación de Alicante tools in Pydantic AI?

Yes, the unified MCPToolset class supports both Streamable HTTP and SSE transports. This lets you connect to the externally hosted Vinkius server without managing raw sockets.

Q: What is the best way to handle unstructured Alicante datasets?

Use the generic getdataset tool to retrieve any raw data table. You can define a custom Pydantic model to parse and validate this unstructured payload before passing it to your LLM.

Validate Alicante municipal datasets at runtime using Pydantic AI and this MCP Server.

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Connect Diputación de Alicante MCP to Pydantic AI

Create your Vinkius account to connect Diputación de Alicante 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 Diputación de Alicante with Pydantic AI

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Enforce strict financial schemas in Pydantic AI

The `get_public_debt` tool retrieves structured Alicante liability metrics that Pydantic AI validates against runtime models. This ensures your agent never processes malformed financial records or corrupt integers. Pair this with `get_municipal_budgets` to build a type-safe fiscal monitor for Alicante towns inside Pydantic AI. If the API returns unexpected data types, your agent fails loudly and immediately, preventing silent data corruption in your database.

Query verified local directories with this MCP Server

The `get_local_directory` tool provides validated contact and location records for Alicante town halls directly to your Pydantic AI agent. This MCP setup removes the risk of your agent hallucinating phone numbers or office addresses. Your Pydantic AI agent can also call `get_cultural_centers` to locate Alicante public facilities. Because every field matches your Pydantic schemas, your downstream geographic mapping code runs without unexpected type errors.

Track municipal events and local festivals

The `get_official_local_festivals` tool delivers validated Alicante scheduling data directly to your Pydantic AI agent loops. This lets you automate regional calendar updates with guaranteed date formats. Use `get_moors_and_christians_festivals` to pull specific cultural event dates across Alicante municipalities. Your Pydantic AI type-safe models parse these strings cleanly, ensuring your travel or logistics agents always receive valid temporal data.

Setup guide

Set up Diputación de Alicante 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": {
        "diputacion-de-alicante-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Diputación de Alicante transactions")
print(result.output)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Diputación de Alicante. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Diputación de Alicante MCP in Pydantic AI

Install the slim package with `pip install "pydantic-ai-slim[mcp]"` and initialize `MCPToolset` with the Vinkius URL. Pass this toolset directly into the `toolsets` list of your Pydantic AI `Agent`.

Yes, every response from tools like `get_municipal_budgets` is validated against Pydantic schemas at runtime. The agent will raise a validation error if the provincial API returns an unexpected data structure.

Yes, the unified `MCPToolset` class supports both Streamable HTTP and SSE transports. This lets you connect to the externally hosted Vinkius server without managing raw sockets.

Use the generic `get_dataset` tool to retrieve any raw data table. You can define a custom Pydantic model to parse and validate this unstructured payload before passing it to your LLM.

All connections use a single secure token that isolates your outbound requests. Vinkius enforces strict network isolation, ensuring your validation schemas and MCP prompts never leave your private runtime.

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