How to Use the GovInfo MCP in LlamaIndex

Q: How does LlamaIndex index GovInfo search results?

Run searchdocuments to pull GovInfo government records, then convert the text payloads into LlamaIndex Document objects. From there, your LlamaIndex pipeline chunks and embeds the GovInfo text into your vector database.

Q: Can I filter GovInfo collections before indexing them in LlamaIndex?

Yes, use listcollections to identify the target GovInfo catalog, then apply date filters using getcollection to retrieve only the specific federal records your LlamaIndex application needs.

Q: How do I setup the GovInfo MCP Server in LlamaIndex?

Instantiate the BasicMCPClient with your Vinkius GovInfo endpoint, convert it with the MCP tool specification, and pass the tools to your LlamaIndex FunctionAgent using totoollistasync().

Q: Does LlamaIndex support real-time federal updates?

Your LlamaIndex agent runs getpublished on a daily cron job to fetch newly released GovInfo documents. This keeps your local LlamaIndex vector index updated with the latest federal publications from GovInfo.

Index official US government records directly into your LlamaIndex vector store using the GovInfo MCP Server.

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Connect GovInfo MCP to LlamaIndex

Create your Vinkius account to connect GovInfo 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 GovInfo with LlamaIndex

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Synthesize GovInfo data in LlamaIndex

The `search_documents` tool queries the official GovInfo database to retrieve structured federal records for your LlamaIndex ingestion pipeline. Your LlamaIndex system converts the raw GovInfo text response into document nodes ready for indexing. By passing these GovInfo nodes to a vector store, your LlamaIndex application builds a searchable knowledge base grounded in actual law. Users query your LlamaIndex index and receive answers backed by direct citations to official GovInfo publications.

Parse deep GovInfo structures with LlamaIndex

The `list_package_granules` tool extracts specific sub-documents from massive GovInfo publications for granular LlamaIndex chunking. Your LlamaIndex ingestion scripts parse individual sections of a GovInfo bill instead of choking on a massive 1,000-page PDF. Using `get_granule_summary` alongside this extraction provides precise GovInfo metadata for each LlamaIndex chunk. LlamaIndex stores these GovInfo summaries as node metadata, ensuring your semantic search queries return highly relevant legal clauses.

Build a GovInfo RAG pipeline with LlamaIndex

The `get_collection` tool gathers entire historical GovInfo collections within a specific date range to feed your LlamaIndex RAG applications. Your LlamaIndex agent compares regulatory shifts over time by indexing GovInfo documents from different years. Query this LlamaIndex index to find related materials by invoking `get_related_documents` to pull linked GovInfo records during retriever execution. This setup lets your LlamaIndex agent build a complete web of federal context for any GovInfo research query.

Setup guide

Set up GovInfo 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 GovInfo 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 GovInfo tools.",
)
response = await agent.run("List recent GovInfo 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 GovInfo. 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 GovInfo MCP in LlamaIndex

Run `search_documents` to pull GovInfo government records, then convert the text payloads into LlamaIndex `Document` objects. From there, your LlamaIndex pipeline chunks and embeds the GovInfo text into your vector database.

Yes, use `list_collections` to identify the target GovInfo catalog, then apply date filters using `get_collection` to retrieve only the specific federal records your LlamaIndex application needs.

Instantiate the `BasicMCPClient` with your Vinkius GovInfo endpoint, convert it with the MCP tool specification, and pass the tools to your LlamaIndex `FunctionAgent` using `to_tool_list_async()`.

Your LlamaIndex agent runs `get_published` on a daily cron job to fetch newly released GovInfo documents. This keeps your local LlamaIndex vector index updated with the latest federal publications from GovInfo.

All GovInfo interactions pass through a secure, ephemeral V8 isolate sandbox on Vinkius. Your GovInfo government document metadata and search queries stay private, processed entirely in a zero-trust MCP environment where credentials never leak to LlamaIndex.

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