How to Use the NavAPI MCP in Pydantic AI

Q: How do I verify NavAPI availability in Pydantic AI?

Call checkapistatus as the first step in your agent flow. It's a quick way to ensure the server is responsive before running expensive queries.

NavAPI provides type-safe maritime data for your Pydantic AI applications.

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Connect NavAPI MCP to Pydantic AI

Create your Vinkius account to connect NavAPI 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 NavAPI with Pydantic AI

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Perplexity

Type-safe maritime route searches

Get runtime validation for every route your agent finds. Using `search_maritime_routes` with Pydantic AI ensures the response matches your expected schema. If the data looks wrong, the agent fails instantly. No silent errors or bad routes reach your production database.

Validate port traffic with Pydantic AI

Grab `get_port_vessel_traffic` results and map them to your own Pydantic models. It forces strict adherence to your data definitions. Your agent only acts on traffic numbers that pass the schema check. It keeps your logistics models clean and predictable.

Strict nautical chart listing

Verify every nautical chart return with `list_nautical_charts`. Pydantic AI rejects any malformed responses before they hit your logic. It makes your agent's navigation decisions rock solid. You stop worrying about unexpected API changes breaking your code.

Setup guide

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

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

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

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Common questions about NavAPI MCP in Pydantic AI

Install the slim MCP package and initialize an MCPToolset with your server URL. Add the toolset to your agent to get type-safe maritime tools.

The agent throws a validation error immediately. It prevents your system from hallucinating or crashing due to bad API responses.

Yes. The toolkit handles Streamable HTTP and SSE transports out of the box. Just point the toolset to your endpoint.

Call `check_api_status` as the first step in your agent flow. It's a quick way to ensure the server is responsive before running expensive queries.

Yes. Each session uses an isolated endpoint token. Your route history and port queries remain private and inaccessible to other users.

Use it with your favorite AI tools

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

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