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How to Use the FCC Geo MCP in LlamaIndex

Index live FCC Geo data into your LlamaIndex knowledge base for grounded, queryable geolocation insights.

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LlamaIndex

Connect FCC Geo MCP to LlamaIndex

Create your Vinkius account to connect FCC Geo 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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Ground your RAG pipeline with FCC Geo

Use `get_census_block_by_lat_lon` to pull raw geographic data into your index. Instead of static files, your agent pulls live regulatory data based on user queries. Everything becomes searchable. The results are indexed alongside your documents for accurate, context-aware responses.

Semantic search across telecommunication zones

The `get_fcc_areas_by_lat_lon` tool maps coordinates to FCC zones. LlamaIndex stores these results, allowing you to query for areas by physical location later. Stop guessing where regions overlap. You have a unified index that ties specific coordinates to their regulatory definitions.

Unified API and document indexing

Combine your private documents with live API output from this MCP server. The agent retrieves the latest data and incorporates it into the current query context. Get answers from facts. Your index reflects real-time FCC data rather than outdated training sets.

Setup guide

Set up FCC Geo MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

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

  2. 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. 3

    Convert to LlamaIndex tools

    Call mcp_tool_spec.to_tool_list_async() to convert all FCC Geo MCP tools into native FunctionTool objects that any LlamaIndex agent can use.

  4. 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 FCC Geo tools.",
)
response = await agent.run("List recent FCC Geo data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by FCC Geo. 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 FCC Geo MCP in LlamaIndex

The server tools return structured data that you convert into index nodes. This allows your RAG application to query locations as if they were part of your document library.
Yes. The tool spec allows the agent to fetch the latest area boundaries whenever a user asks a location-based question.
The server only processes coordinate pairs. No sensitive user data leaves your local index environment.
You get back FIPS codes, census blocks, and FCC service areas. These are raw text and numeric strings ready for vectorization.
You can use the allowed_tools filter to restrict which parts of the FCC data are accessible to your agent.

Start using the FCC Geo MCP today

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