How to Use the BCLaws API MCP in LangChain

Q: How can my LangChain agent find a specific section of a BC statute using the BCLaws API?

Your agent should first use searchbclaws to find the statute's ID. Then, it can pass that ID to getbcstatute to retrieve the full text and process it to find the specific section.

Q: What's the best way to get a list of all available acts with the BCLaws API in LangChain?

The most direct way is to have your agent call the listbcacts tool. It requires no parameters and returns a complete list, which you can then use as input for other tools in your chain.

Build legal research agents in LangChain that can navigate British Columbia law, from high-level acts to specific regulations.

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Connect BCLaws API MCP to LangChain

Create your Vinkius account to connect BCLaws API to LangChain 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 LangChain

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Chain legal lookups together

This server gives your LangChain agent tools to perform multi-step legal research. You can build a chain where an agent first calls `list_bc_acts` to see what's available, then uses that output to inform a `search_bc_laws` call for a specific topic. It's a logical, step-by-step process. Because it's LangChain, the output of one tool call becomes the input for the next. An agent can find a statute ID with a search, then immediately pass that ID to `get_bc_statute` to fetch the full text. You can trace the entire reasoning sequence in LangSmith to see exactly how your agent arrived at its conclusion.

Drill down into statutes and regulations

Go from broad searches to the exact text you need. Once your agent identifies a relevant law using `search_bc_laws`, it can use its reasoning ability to decide whether to call `get_bc_statute` or `get_bc_regulation`. This isn't just a simple API call; it's an autonomous decision made within your agent's logic. This is perfect for building agents that can answer specific questions. Instead of just getting a list of search results, your agent gets the actual content of the law. You can then have it summarize the text, extract key points, or compare different sections, all within a single, observable chain.

Monitor and list laws with your LangChain MCP Server

Sometimes you just need a quick status check or a complete list. This MCP Server includes simple tools for just that. You can build a simple agent that periodically runs `check_api_status` to make sure the BCLaws API is online before kicking off a longer research task. It's a simple but effective way to build more resilient chains. Your agent can also use `list_consolidated_laws` to pull a full catalog of current statutes and regulations. This is useful for discovery or for creating a starting point for a more detailed investigation. These utility tools give your agents more context and control over their environment.

Setup guide

Set up BCLaws API MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes BCLaws API tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "bclaws-api-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent BCLaws API transactions"
    })
    print(result["messages"][-1].content)

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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 BCLaws API. 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 BCLaws API MCP in LangChain

Your agent should first use `search_bc_laws` to find the statute's ID. Then, it can pass that ID to `get_bc_statute` to retrieve the full text and process it to find the specific section.

Yes. When you connect your agent to this MCP Server, every tool call—like `get_bc_regulation`—is automatically captured in LangSmith traces. You'll see the inputs, outputs, and latency for each step.

The most direct way is to have your agent call the `list_bc_acts` tool. It requires no parameters and returns a complete list, which you can then use as input for other tools in your chain.

Yes, you can use these tools within a multi-agent framework like LangGraph. For example, one agent could be responsible for searching with `search_bc_laws`, while another agent validates findings using `get_bc_statute`.

The server only processes public record data, specifically British Columbia statutes and regulations. Your connection runs in a Vinkius V8 isolate sandbox, which is ephemeral and memory-safe, ensuring your session's queries are isolated and destroyed after use.

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