How to Use the BCLaws API MCP in LlamaIndex

Q: How do I index all BC regulations into a vector store with the BCLaws API and LlamaIndex?

First, use the listconsolidatedlaws tool to get a list of all regulations. Then, create a loop that calls getbcregulation for each item and passes the resulting text into your LlamaIndex ingestion pipeline to populate your vector store.

Q: Can a LlamaIndex agent decide between searching live or using the index for the BCLaws API?

Yes. You can configure a FunctionAgent in LlamaIndex with both the MCP tools and a query engine tool for your index. The agent will then choose whether to call searchbclaws for live data or query the index based on the user's prompt.

Q: What's the setup process for this MCP Server with LlamaIndex?

It's straightforward. After installing llama-index-tools-mcp, you instantiate the BasicMCPClient with your Vinkius URL. Then, wrap it in the McpToolSpec and call totoollistasync() to get a list of tools to pass to your agent.

Use LlamaIndex to build a RAG system over the live BCLaws API, grounding answers in actual, up-to-date legal text.

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Connect BCLaws API MCP to LlamaIndex

Create your Vinkius account to connect BCLaws API to LlamaIndex 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 LlamaIndex

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Index BC laws into a knowledge base

Turn the BCLaws API into a queryable knowledge base. You can use the MCP tools to fetch legal documents—for instance, by calling `list_bc_acts` and then looping through the results with `get_bc_statute`—and have LlamaIndex automatically index the text into your chosen vector store. This creates a local, searchable copy of BC law. Once indexed, this data becomes the foundation for your RAG application. You're no longer limited to simple keyword searches. You can now perform semantic searches to find conceptually related laws and regulations, even if they don't use the same terminology.

Get grounded answers from legal text

Ask questions in plain English and get answers backed by specific legal documents. When you query your LlamaIndex application, it finds the most relevant text chunks from the laws you've indexed—data originally fetched with tools like `get_bc_regulation` or `get_bc_statute`. This context is then passed to the LLM. The result is an answer that isn't a hallucination. The system can cite the exact source of its information, linking back to the specific statute or regulation that informed the response. It's a reliable way to build legal Q&A bots.

Combine keyword and semantic search

Get the best of both worlds for legal discovery. You can use the `search_bc_laws` tool for precise keyword matching when you know exactly what you're looking for, like a specific document number or title. This is handled as a direct tool call through your LlamaIndex agent. For broader, concept-based questions, you can query the vector index you've already built. This hybrid approach lets you build more sophisticated applications. Your agent can decide whether a direct API call or a query against the indexed knowledge base is the right tool for the job.

Setup guide

Set up BCLaws API MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all BCLaws API MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to BCLaws API tools.",
)
response = await agent.run("List recent BCLaws API data")

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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 LlamaIndex

First, use the `list_consolidated_laws` tool to get a list of all regulations. Then, create a loop that calls `get_bc_regulation` for each item and passes the resulting text into your LlamaIndex ingestion pipeline to populate your vector store.

Yes. You can configure a `FunctionAgent` in LlamaIndex with both the MCP tools and a query engine tool for your index. The agent will then choose whether to call `search_bc_laws` for live data or query the index based on the user's prompt.

Not automatically. You need to set up a process to periodically re-fetch and re-index the data using the BCLaws API tools. You could, for example, run a daily job that calls `list_consolidated_laws` and updates your index with any changes.

It's straightforward. After installing `llama-index-tools-mcp`, you instantiate the `BasicMCPClient` with your Vinkius URL. Then, wrap it in the `McpToolSpec` and call `to_tool_list_async()` to get a list of tools to pass to your agent.

The BCLaws API provides public statutes and regulations, so the data itself is not private. However, your indexed copy of this data is under your control. The Vinkius MCP Server secures the connection for fetching the data, but you are responsible for securing the vector database where you store the resulting index.

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