How to Use the IBAMA Dados Abertos MCP in Pydantic AI

Q: Can my Pydantic AI agent perform a search on IBAMA Dados Abertos?

Yes, you use the searchdatasets tool. Your agent can pass search terms as parameters and receive a validated list of results.

Q: How do I list organizations within IBAMA Dados Abertos using Pydantic AI?

You call the listorganizations tool. Your agent receives the data, which is then validated against your organization model, allowing for safe and structured processing.

Run type-safe environmental data queries with IBAMA Dados Abertos and Pydantic AI for guaranteed schema compliance.

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Connect IBAMA Dados Abertos MCP to Pydantic AI

Create your Vinkius account to connect IBAMA Dados Abertos 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 IBAMA Dados Abertos with Pydantic AI

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Type-safe extraction of IBAMA Dados Abertos

Every response from `datastore_search` is validated against your Pydantic models at runtime. If the portal returns a malformed record, your Pydantic AI agent catches it immediately. This prevents silent errors in your compliance pipeline. You define the expected structure, and the system enforces it, ensuring your environmental data is always clean and ready for analysis.

Execute precise dataset searches

Use `search_datasets` to find the exact environmental registry you need. Your agent provides the query string, and the server returns a list of datasets that match your defined parameters. Your agent then selects the best candidate for further inspection. Because you are using Pydantic AI, the search results are validated before they ever touch your business logic.

Detailed resource metadata inspection

Call `show_resource` to pull granular file information. This provides your agent with the necessary context—such as file format and record count—to decide if the resource is suitable for your current task. This level of detail is necessary for high-stakes compliance work. You verify everything before proceeding, using the strict validation of your models to guarantee that only accurate data enters your system.

Setup guide

Set up IBAMA Dados Abertos 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": {
        "ibama-dados-abertos-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent IBAMA Dados Abertos transactions")
print(result.output)

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Common questions about IBAMA Dados Abertos MCP in Pydantic AI

You define Pydantic models for the tool outputs. The framework validates every response against these models, ensuring that any data returned from the portal matches your strict requirements.

Yes, you use the `search_datasets` tool. Your agent can pass search terms as parameters and receive a validated list of results.

You call the `list_organizations` tool. Your agent receives the data, which is then validated against your organization model, allowing for safe and structured processing.

Pydantic AI will raise a validation error. This forces your agent to handle the failure explicitly, preventing corrupt data from moving downstream.

The server uses an isolated sandbox environment. It fetches public environmental information via standard HTTPS, ensuring no sensitive data is exchanged and your agent remains secure.

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