Do I need an API key?

No! Overpass API is completely free and open. No authentication required. Please be respectful with query sizes — avoid queries returning more than 10,000 elements.

What is a bounding box?

A bounding box defines a geographic area using min_latitude, min_longitude, max_latitude, max_longitude. Example: "40.70,-74.01,40.72,-73.98" covers Lower Manhattan, NYC.

Can I search near my current location?

Yes! Use search_nearby or search_nearby_amenities with your GPS coordinates and a radius in meters (e.g. lat=40.7128, lon=-74.0060, radius=1000 for 1km around NYC).

What amenities can I search for?

Common amenities: restaurant, cafe, fast_food, bar, pub, hospital, clinic, pharmacy, school, university, library, atm, bank, fuel, parking, police, fire_station, post_office, toilets, cinema, theatre, nightclub, museum.

Overpass (OpenStreetMap) MCP Server for Pydantic AI 16 tools — connect in under 2 minutes

Name: Overpass (OpenStreetMap)
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 16 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Overpass (OpenStreetMap) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Overpass (OpenStreetMap) "
            "(16 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Overpass (OpenStreetMap)?"
    )
    print(result.data)

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 Overpass (OpenStreetMap) MCP Server

Connect to Overpass API (OpenStreetMap) and query the world's largest free geographic database through natural conversation — no API key needed.

Pydantic AI validates every Overpass (OpenStreetMap) tool response against typed schemas, catching data inconsistencies at build time. Connect 16 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Amenity Search — Find restaurants, cafes, hospitals, schools, pharmacies, ATMs, fuel stations and more
Shop Search — Discover shops, supermarkets, bakeries, clothing stores and retail outlets
Nearby Search — Find any amenity within a radius of any GPS coordinate
Hotel Search — Locate hotels, hostels and tourist accommodation
Park Search — Find parks, gardens and green spaces
EV Charging — Locate electric vehicle charging stations
Custom Queries — Execute custom Overpass QL queries for any OSM data

The Overpass (OpenStreetMap) MCP Server exposes 16 tools through the Vinkius. Connect it to Pydantic AI 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 Overpass (OpenStreetMap) to Pydantic AI via MCP

Follow these steps to integrate the Overpass (OpenStreetMap) MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

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 16 tools from Overpass (OpenStreetMap) with type-safe schemas

Why Use Pydantic AI with the Overpass (OpenStreetMap) MCP Server

Pydantic AI provides unique advantages when paired with Overpass (OpenStreetMap) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Overpass (OpenStreetMap) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Overpass (OpenStreetMap) connection logic from agent behavior for testable, maintainable code

Overpass (OpenStreetMap) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Overpass (OpenStreetMap) MCP Server delivers measurable value.

Type-safe data pipelines: query Overpass (OpenStreetMap) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Overpass (OpenStreetMap) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Overpass (OpenStreetMap) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Overpass (OpenStreetMap) responses and write comprehensive agent tests

Overpass (OpenStreetMap) MCP Tools for Pydantic AI (16)

These 16 tools become available when you connect Overpass (OpenStreetMap) to Pydantic AI via MCP:

custom_query

The query should be valid Overpass QL syntax. The output format is automatically set to JSON. If no out statement is included, "out geom;" is appended automatically. Example: `node["amenity"="cafe"](51.5,-0.15,51.51,-0.14); out geom;` Execute a custom Overpass QL query

search_amenities

Common amenities: "restaurant", "cafe", "school", "hospital", "pharmacy", "bank", "atm", "fuel", "parking", "toilets", "library", "police", "fire_station", "post_office", "cinema", "theatre", "nightclub", "bar", "pub", "fast_food", "ice_cream". Bbox format: lat_min,lon_min,lat_max,lon_max. Search for amenities (restaurants, schools, hospitals, etc.) in a bounding box

search_atms

Returns ATM locations, operator/bank names, addresses, 24/7 availability and network info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for ATMs in a bounding box

search_by_name

Optional amenity filter to narrow results. Returns matching elements with full details including addresses, phone numbers and websites. Search for OSM elements by name

search_by_tag

Bbox format: lat_min,lon_min,lat_max,lon_max (e.g. "51.249,-0.15,51.251,-0.10" for central London). Useful for finding specific OSM-tagged features. Search OpenStreetMap elements by tag key/value in a bounding box

search_charging_stations

Returns station names, addresses, connector types, charging speeds, operator info and access details. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for EV charging stations in a bounding box

search_fuel_stations

Returns station names, brands, addresses, fuel types offered, opening hours and operator info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for fuel/gas stations in a bounding box

search_hospitals

Returns facility names, addresses, phone numbers, emergency services info, specialties and operator info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for hospitals and clinics in a bounding box

search_hotels

Returns hotel names, addresses, star ratings, phone numbers, websites and room info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for hotels in a bounding box

search_nearby

Useful for finding nearby amenities without defining a full bounding box. Returns names, addresses, distances and details. Search for OSM elements near a specific location

search_nearby_amenities

Common amenities: "restaurant", "cafe", "pharmacy", "atm", "bank", "hospital", "school", "supermarket", "fuel", "charging_station", "parking", "toilets", "police", "fire_station", "post_office". Search for specific amenities near a location

search_parks

Returns park names, addresses, area sizes, features (playgrounds, sports facilities) and operator info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for parks and green spaces in a bounding box

search_pharmacies

Returns pharmacy names, addresses, phone numbers, opening hours, dispensing info and operator info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for pharmacies in a bounding box

search_restaurants

Optional cuisine filter: "italian", "chinese", "japanese", "indian", "mexican", "thai", "french", "american", "pizza", "burger", "sushi", "vegan", "vegetarian". Bbox format: lat_min,lon_min,lat_max,lon_max. Search for restaurants in a bounding box

search_schools

Returns school names, addresses, phone numbers, websites, student capacity and operator info. Bbox format: lat_min,lon_min,lat_max,lon_max. Search for schools in a bounding box

search_shops

Optional shop type filter: "supermarket", "convenience", "clothes", "bakery", "butcher", "electronics", "furniture", "hardware", "jewelry", "mall", "bookmaker", "car", "car_repair", "chemist", "florist", "gift", "hairdresser", "mobile_phone", "shoes", "sports", "toys". Bbox format: lat_min,lon_min,lat_max,lon_max. Search for shops in a bounding box

Example Prompts for Overpass (OpenStreetMap) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Overpass (OpenStreetMap) immediately.

"Find all restaurants in Lower Manhattan."

"Find ATMs within 500m of Times Square (40.7580, -73.9855)."

"Find EV charging stations in downtown San Francisco."

Troubleshooting Overpass (OpenStreetMap) MCP Server with Pydantic AI

Common issues when connecting Overpass (OpenStreetMap) to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Overpass (OpenStreetMap) + Pydantic AI FAQ

Common questions about integrating Overpass (OpenStreetMap) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Overpass (OpenStreetMap) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.