How accurate is the geocoding — can I use it for delivery routing?

OpenCage returns a confidence score from 1 to 10 for each result. Use the high-confidence filter (min_confidence=8 or higher) to get delivery-grade accuracy. Combined with country filtering, you can eliminate ambiguous matches and get coordinates reliable enough for last-mile dispatch.

What does privacy mode actually do?

When you enable no_record=1, OpenCage processes your query but doesn't log it in their cache or analytics. The result is identical, but the query leaves no trace on their servers. Ideal for geocoding patient addresses, legal documents, or any PII-sensitive data.

Can I geocode in multiple languages — like getting results in Portuguese for a Brazilian address?

Yes. Use the language bias tool with any IETF language code (pt-BR, es-MX, fr-FR, etc.) and OpenCage returns the address components translated to that locale. Perfect for building multilingual apps or standardizing address formats across regions.

OpenCage MCP Server for LangChain 10 tools — connect in under 2 minutes

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect OpenCage through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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({
        "opencage": {
            "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 OpenCage, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 OpenCage MCP Server

Give your AI agent precise geolocation superpowers with OpenCage Geocoding. Convert any address into coordinates, reverse-geocode GPS pins into readable addresses, and apply advanced filters — all through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with OpenCage through native MCP adapters. Connect 10 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

Forward Geocoding — Convert any address or place name into exact latitude/longitude coordinates
Reverse Geocoding — Turn GPS coordinates into structured street addresses with timezone and sun data
Country Filtering — Restrict results to a specific country (ISO 3166-1 Alpha-2) to avoid ambiguous city matches
Language Bias — Request results localized in any IETF language code (e.g., pt-BR, fr-FR)
Confidence Scoring — Filter geocoding results by minimum confidence level (1–10) for delivery-grade accuracy
Bounding Box — Constrain results to a geographic rectangle for targeted regional searches
Privacy Mode — Run geocoding queries without OpenCage logging them, for sensitive addresses
Duplicate Control — Return or suppress duplicate results for data validation workflows

The OpenCage MCP Server exposes 10 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 OpenCage to LangChain via MCP

Follow these steps to integrate the OpenCage 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 10 tools from OpenCage via MCP

Why Use LangChain with the OpenCage MCP Server

LangChain provides unique advantages when paired with OpenCage through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine OpenCage 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 OpenCage queries for multi-turn workflows

OpenCage + LangChain Use Cases

Practical scenarios where LangChain combined with the OpenCage MCP Server delivers measurable value.

RAG with live data: combine OpenCage tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query OpenCage, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain OpenCage tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every OpenCage tool call, measure latency, and optimize your agent's performance

OpenCage MCP Tools for LangChain (10)

These 10 tools become available when you connect OpenCage to LangChain via MCP:

geocode_all_duplicate_results

Retrieve the exact structural matching verifying Delivery alternatives

geocode_basic

Identify bounded routing spaces inside the Headless OpenCage Engine

geocode_bounding_box

Inspect deep internal arrays mitigating specific Polygon domains

geocode_country_filter

Perform structural extraction of properties driving active Country nodes

geocode_high_confidence

Dispatch an automated validation check routing explicit Score limits

geocode_language_bias

Retrieve explicit Cloud logging tracing explicit Payload locales

geocode_no_record_privacy

Provision a highly-available JSON Payload generating secure mappings

reverse_basic

Enumerate explicitly attached structured rules exporting active GPS pins

reverse_fast_no_annotations

Identify precise active arrays spanning native Location limits faster

reverse_fetch_time_annotations

Irreversibly vaporize explicit validation limits extracting UTC logic

Example Prompts for OpenCage in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with OpenCage immediately.

"What are the coordinates for 1600 Amphitheatre Parkway, Mountain View, CA?"

"What's at coordinates 48.8566, 2.3522?"

"Geocode 'Springfield' but only show results in the United States with confidence >= 7."

Troubleshooting OpenCage MCP Server with LangChain

Common issues when connecting OpenCage to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

OpenCage + LangChain FAQ

Common questions about integrating OpenCage MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.