Google Maps MCP Server for LangChain 4 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Google Maps through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"google-maps": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Google Maps, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Google Maps MCP Server
Connect your Google Maps Platform account to any AI agent and take full control of your geospatial intelligence, place discovery, and routing through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Google Maps through native MCP adapters. Connect 4 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Geocoding Orchestration — Convert physical addresses or location names into precise geographic coordinates (Latitude/Longitude) translating human readable locations into spatial API bounds flawlessly
- Place Discovery — Finds physical entities within Google Maps database matching text queries like 'Restaurants in New York', retrieving critical PlaceIDs for deep introspection natively
- Rich Metadata Retrieval — Retrieve deep details of specific places including phone numbers, user reviews, opening hours, and websites using PlaceIDs to bypass generic search arrays synchronously
- Route & ETA Calculation — Triggers routing engine identifying physical transit maps resolving directions, distance, and optimal time calculations between origin and destination bounds flawlessly
- Travel Mode Support — Execute directions queries for driving, walking, bicycling, or transit modes to verify travel logistics and ETAs synchronously across your environment
- Geospatial Intelligence — Analyze specific localized coordinates to verify presence and proximity of businesses or landmarks within the Google Maps ecosystem securely
The Google Maps MCP Server exposes 4 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Google Maps to LangChain via MCP
Follow these steps to integrate the Google Maps MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 4 tools from Google Maps via MCP
Why Use LangChain with the Google Maps MCP Server
LangChain provides unique advantages when paired with Google Maps through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Google Maps MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Google Maps queries for multi-turn workflows
Google Maps + LangChain Use Cases
Practical scenarios where LangChain combined with the Google Maps MCP Server delivers measurable value.
RAG with live data: combine Google Maps tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Google Maps, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Google Maps tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Google Maps tool call, measure latency, and optimize your agent's performance
Google Maps MCP Tools for LangChain (4)
These 4 tools become available when you connect Google Maps to LangChain via MCP:
directions
Calculate ETA, distance, and optimal route directions between origin and destination
geocode
Convert an address or location name into precise geographic coordinates (Latitude / Longitude)
place_details
Get deep details of a specific Place (Phone number, reviews, opening hours, website) using its PlaceID
place_search
Search for businesses, restaurants, or spots (e.g. "Pizza in New York", "Hospitals near me")
Example Prompts for Google Maps in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Google Maps immediately.
"Geocode this address: '1600 Amphitheatre Pkwy, Mountain View, CA'"
"Find pizza restaurants in Brooklyn and show me details for the best one"
"Get directions from San Francisco to San Jose by train"
Troubleshooting Google Maps MCP Server with LangChain
Common issues when connecting Google Maps to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGoogle Maps + LangChain FAQ
Common questions about integrating Google Maps MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Google Maps with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Google Maps to LangChain
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.