Mapillary MCP Server for LangChain 7 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Mapillary 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({
"mapillary": {
"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 Mapillary, 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 Mapillary MCP Server
Connect to Mapillary and access the world's largest street-level imagery platform through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Mapillary through native MCP adapters. Connect 7 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
- Image Search — Search street-level images by geographic bounding box
- Image Details — Get image metadata including GPS coordinates, capture date, compass angle and sequence
- Sequence Search — Find image sequences (connected images along routes) by area
- Map Features — Search detected traffic signs, objects and road markings by area
- Object Detections — Get all detected objects in a specific image
The Mapillary MCP Server exposes 7 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 Mapillary to LangChain via MCP
Follow these steps to integrate the Mapillary 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 7 tools from Mapillary via MCP
Why Use LangChain with the Mapillary MCP Server
LangChain provides unique advantages when paired with Mapillary through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Mapillary 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 Mapillary queries for multi-turn workflows
Mapillary + LangChain Use Cases
Practical scenarios where LangChain combined with the Mapillary MCP Server delivers measurable value.
RAG with live data: combine Mapillary tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Mapillary, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Mapillary tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Mapillary tool call, measure latency, and optimize your agent's performance
Mapillary MCP Tools for LangChain (7)
These 7 tools become available when you connect Mapillary to LangChain via MCP:
get_detection_value
Returns the detected value, type, GPS coordinates and image association. Get details for a specific object detection
get_image
Returns image ID, capture date/time, GPS coordinates, compass angle, sequence ID, organization and thumbnail URL. Use fields parameter to request additional data like "geometry,compass_angle,captured_at,sequence,thumb_256_url,thumb_1024_url,altitude". Get details for a specific Mapillary image
get_image_detections
Returns detection values, types, geometry and confidence scores. Get object detections for a specific image
get_map_features
Returns feature type, value, GPS coordinates and detection confidence. Useful for traffic sign inventory and road infrastructure analysis. Search map features (traffic signs, objects) by area
get_sequence
Returns sequence ID, creation date and related images. Get details for a specific image sequence
search_images
Returns image IDs, coordinates, capture dates, compass angles and sequence IDs. Bbox format: min_lon,min_lat,max_lon,max_lat (e.g. "-0.15,51.50,-0.10,51.52" for central London). Search street-level images by geographic area
search_sequences
Returns sequence IDs and metadata for all sequences that pass through the area. Search image sequences by geographic area
Example Prompts for Mapillary in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Mapillary immediately.
"Find street-level images in central London."
"Search for traffic signs in São Paulo."
"Get object detections for image abc123."
Troubleshooting Mapillary MCP Server with LangChain
Common issues when connecting Mapillary to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMapillary + LangChain FAQ
Common questions about integrating Mapillary 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 Mapillary 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 Mapillary to LangChain
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.