How to Use the Impala MCP in Pydantic AI

Q: Can I get hotel reviews for Pydantic AI using Impala?

You can. The getreviews tool returns data that your agent can validate and summarize for your users.

Get type-safe hotel data for Pydantic AI agents with Impala integration.

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Connect Impala MCP to Pydantic AI

Create your Vinkius account to connect Impala 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 Impala with Pydantic AI

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Type-safe hotel search for Pydantic AI

Every search result from `search_hotels` and `search_hotels_by_city` is validated against your models. If the data structure is wrong, your agent catches it immediately. This keeps your agent logic clean. You don't have to worry about unexpected fields or missing data crashing your process.

Validate rates in Pydantic AI

Use `check_availability` and `get_rates` with strict schema enforcement. Your agent expects a specific format, and this server delivers it every time. If the API returns bad data, the agent halts before a booking error occurs. You get a clear validation error instead of silent data corruption.

Fetch hotel details into Pydantic AI

Load property information, photos, and reviews using `get_hotel`, `get_photos`, and `get_reviews`. Your agent handles these as typed objects. This makes building complex agent workflows safer. You know exactly what the data looks like before you use it to answer a user.

Setup guide

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

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

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

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Common questions about Impala MCP in Pydantic AI

You define your toolset and pass it to the agent. Then, your Pydantic AI agent can trigger a search and validate the results against your schemas.

No. Pydantic AI will catch the validation error, preventing the agent from acting on corrupt or missing information.

You can. The `get_reviews` tool returns data that your agent can validate and summarize for your users.

It does. This allows for persistent, stable connections between your running agent and the hotel platform.

The server acts as a strictly defined gateway. Only the data you explicitly request is transmitted, and all interactions are authenticated via your endpoint token.

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