How to Use the BCLaws API MCP in Pydantic AI

Validate BCLaws API responses with Pydantic AI for strict legal compliance.

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Connect BCLaws API MCP to Pydantic AI

Create your Vinkius account to connect BCLaws API 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 BCLaws API with Pydantic AI

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Type-safe law searching in Pydantic AI

Execute `search_bc_laws` to find relevant regulations, with the results immediately validated against your Pydantic models. If the API returns garbage, your agent stops before processing bad data. This setup forces the agent to respect the schema. It eliminates the risk of hallucinated fields during your legal research tasks.

Audit regulations with Pydantic AI

Use `get_bc_regulation` to pull and verify specific clauses. Every response is checked against your defined types, ensuring that the legal text is structured exactly as your logic expects. Your agent fails fast if the data doesn't match. It saves you from debugging silent errors in your document processing pipeline.

Monitor BCLaws API health in Pydantic AI

Run `check_api_status` to ensure the server is responsive. You incorporate this into your Pydantic AI agent's startup sequence to verify the environment is ready. It provides a clean, typed boolean response. Your agent uses this to decide whether to proceed with complex queries.

Setup guide

Set up BCLaws API 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": {
        "bclaws-api-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about BCLaws API MCP in Pydantic AI

You get runtime validation for every law query. Pydantic AI ensures that the API output matches your expected data structure perfectly.

The MCPToolset supports both Streamable HTTP and SSE. These are robust transports for your Pydantic AI agent.

Install the slim package with MCP support. Then, pass the MCPToolset to your Agent instance to connect.

Yes, the server must run externally. You point the toolset at the URL, and your agent handles the rest.

Your agent pulls public statutes only. The connection is encrypted and token-gated to prevent any data leakage from your private logic.

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