How to Use the Google Maps Platform MCP in LlamaIndex
Index live Google Maps routes, place data, and geocodes directly into your LlamaIndex vector store for RAG.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Google Maps Platform MCP to LlamaIndex
Create your Vinkius account to connect Google Maps Platform 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.
Index Live Place Data with LlamaIndex
The `get_place_details` tool feeds rich metadata directly into your LlamaIndex vector store. When your agent calls this tool or `search_nearby_places`, the returned location metadata is indexed directly into your vector store. This lets you run semantic searches over physical business details and reviews. You can query past discovery sessions without hitting the external API again. The agent looks up previously indexed spatial data first, saving API credits while keeping your application grounded in verified location facts.
Ground Routing Queries in Vector Storage
The `get_directions` tool fetches active transit or driving routes to index alongside your historical logs in LlamaIndex. Combine historical route logs with live data. When calculating complex logistics, the agent queries this unified index. It compares live distance calculations from `get_distance_matrix` with past performance data to generate accurate ETA predictions that are free from LLM hallucinations.
Geocoding and Elevation Data Indexing
The `geocode_address` tool maps physical locations to coordinate profiles inside your LlamaIndex document store. The agent uses this tool and `get_elevation` to map physical locations, then writes those coordinate profiles into your LlamaIndex document store. This allows your RAG application to answer complex spatial queries. The agent can retrieve elevation profiles and timezone details from `get_timezone` to contextualize physical site assessments.
Set up Google Maps Platform MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 Google Maps Platform MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 Google Maps Platform tools.",
)
response = await agent.run("List recent Google Maps Platform data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Maps Platform. 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 Google Maps Platform MCP in LlamaIndex
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