How to Use the BOE (Boletín Oficial del Estado) MCP in LlamaIndex

Q: Are previous relations available for indexing?

Yes. You use listpreviousrelations to build a graph of how laws evolve over time. This creates a rich context for your agents.

Index Spanish legal history into LlamaIndex for RAG-based document retrieval.

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Connect BOE (Boletín Oficial del Estado) MCP to LlamaIndex

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Setup BOE (Boletín Oficial del Estado) with LlamaIndex

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Ground LlamaIndex in official law

Use `get_legislation_text` to pull full legal documents directly into your LlamaIndex vector store. You eliminate hallucinations by forcing your agent to index the actual text of the law. It turns static government records into a searchable knowledge base.

Automate BOE (Boletín Oficial del Estado) indexing

The `list_subjects` and `list_scopes` tools help you categorize legislation before adding it to your index. Your LlamaIndex pipeline maps these categories to your vector metadata. This makes your retrieval significantly more accurate than standard keyword searches.

Verify legislation with LlamaIndex

Fetch current status using `list_consolidation_states` to ensure your RAG application uses the latest version of a law. Your agents check these states before answering user questions. It keeps your knowledge base current with the official gazette.

Setup guide

Set up BOE (Boletín Oficial del Estado) 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 BOE (Boletín Oficial del Estado) 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 BOE (Boletín Oficial del Estado) tools.",
)
response = await agent.run("List recent BOE (Boletín Oficial del Estado) data")

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Common questions about BOE (Boletín Oficial del Estado) MCP in LlamaIndex

Yes. You pass the text returned by this MCP Server into your LlamaIndex ingestion pipeline. It converts legal text into embeddings automatically.

You use the search tools to find relevant IDs, then pull the full text. This data becomes part of your local index for semantic queries.

Absolutely. You can include ELI metadata in your nodes to keep track of legal identifiers. This helps your RAG system filter by date or rank.

Yes. You use `list_previous_relations` to build a graph of how laws evolve over time. This creates a rich context for your agents.

This server retrieves public legislative information only. No private user data touches the index, ensuring your local RAG stays clean.

Use it with your favorite AI tools

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

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