Nominatim MCP Server for LlamaIndex 5 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Nominatim as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Nominatim. "
"You have 5 tools available."
),
)
response = await agent.run(
"What tools are available in Nominatim?"
)
print(response)
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 Nominatim MCP Server
Connect to Nominatim and search the world's most comprehensive open-source geographic database through natural conversation — no API key needed.
LlamaIndex agents combine Nominatim tool responses with indexed documents for comprehensive, grounded answers. Connect 5 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Address Search — Find any place by name, address or type of place (restaurants, schools, hospitals)
- Reverse Geocoding — Convert GPS coordinates to human-readable addresses
- OSM Lookup — Look up detailed info for any OpenStreetMap object by its ID
- Structured Addresses — Get detailed address components (street, city, state, postal code, country)
- Multi-language Names — Retrieve place names in different languages
- Bounding Boxes — Get geographic boundaries for cities, countries and regions
The Nominatim MCP Server exposes 5 tools through the Vinkius. Connect it to LlamaIndex 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 Nominatim to LlamaIndex via MCP
Follow these steps to integrate the Nominatim MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 5 tools from Nominatim
Why Use LlamaIndex with the Nominatim MCP Server
LlamaIndex provides unique advantages when paired with Nominatim through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Nominatim tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Nominatim tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Nominatim, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Nominatim tools were called, what data was returned, and how it influenced the final answer
Nominatim + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Nominatim MCP Server delivers measurable value.
Hybrid search: combine Nominatim real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Nominatim to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Nominatim for fresh data
Analytical workflows: chain Nominatim queries with LlamaIndex's data connectors to build multi-source analytical reports
Nominatim MCP Tools for LlamaIndex (5)
These 5 tools become available when you connect Nominatim to LlamaIndex via MCP:
get_details
Returns the object's full name, display name, place rank, importance score, bounding box, parent place hierarchy, linked Wikipedia/Wikidata articles and optional extratags. OSM type: N (node), W (way), R (relation). Get detailed info for an OSM object
get_status
Returns status message and response latency. Useful for verifying the service is operational before making other requests. Get Nominatim server status
lookup_osm
IDs are formatted as "type{id}" where type is N (node), W (way) or R (relation). Multiple IDs are comma-separated. Returns the object's display name, coordinates, bounding box and properties. Look up OSM objects by ID
reverse_geocode
Returns the nearest address, city, state, country and other location details. Supports different zoom levels for varying detail granularity. Convert coordinates to an address
search
Returns results with coordinates, bounding box, display name, address components and OSM type/id. Supports structured searches with country codes and viewbox for region prioritization. Rate limited to 1 request/second. Search for places by name or address
Example Prompts for Nominatim in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Nominatim immediately.
"Find the coordinates for the Eiffel Tower."
"What address is at coordinates 40.7128, -74.0060?"
"Search for 'Central Park' and show me its bounding box."
Troubleshooting Nominatim MCP Server with LlamaIndex
Common issues when connecting Nominatim to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpNominatim + LlamaIndex FAQ
Common questions about integrating Nominatim MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Nominatim 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 Nominatim to LlamaIndex
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.