# Pelias Geocoder MCP for AI Agents AI Agent Connect

> Pelias Geocoder lets your AI client turn messy addresses into precise coordinates and vice versa. It handles autocomplete for places, filters by country or bounding box, and pulls structural data from the Pelias Geocoding Platform. It’s the bridge between human-readable locations and the raw geospatial data your apps need to function.

## Overview
- **Category:** developer-tools
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_9xauhtmLx4FJnpssXKIJfawJuO9h0Fd6rFMjRoZ7/ai-agent-connect
- **Tags:** geocoding, reverse-geocoding, poi-search, autocomplete, map-data, spatial-analysis

## Description

Imagine you're building a delivery app and need to know exactly where "The Corner Store" is located. Usually, you'd have to juggle multiple API calls, handle messy strings, and deal with inconsistent results from different map providers. This Connector changes that by giving your agent direct access to the Pelias Geocoding Platform. Instead of just guessing, your AI can now pull structured bounding boxes, filter results by specific countries, or find nearby points of interest with a set distance limit. It handles the heavy lifting of spatial logic so you can focus on the actual app features. Whether you're cleaning up a massive list of addresses or building a real-time search bar, this tool makes the data reliable. It's one of the many high-quality tools you can find in the Vinkius catalog to make your AI-powered workflows actually useful in the real world. You get clean JSON, consistent results, and the ability to bias searches toward specific areas without breaking your logic. You can process thousands of location queries without worrying about whether the results will stay within your target region or if the address formatting will break your database. It turns your agent into a production-ready geospatial engine that understands the difference between a street name and a coordinate.

## Tools

### search_geocode
Find the exact coordinates for a specific address or location name.

### search_bounding_box
Identify every geometry that falls within a specific rectangular area.

### search_country_filter
Get localized results that only show up within specific country boundaries.

### search_autocomplete
Get real-time location suggestions based on what a user is typing in a search bar.

### lookup_place_id
Pull all available properties and rich data for a specific place ID.

### reverse_geocode
Convert latitude and longitude coordinates into a readable street address.

### reverse_distance_limit
Find nearby locations within a specific radius from a set point.

### search_focus_bias
Prioritize search results that are physically closer to a specific GPS point.

### search_layer_filter
List and export active GIS datasets from the attached structured rules.

### structured_geocoding
Isolate specific terms like regions or addresses to find precise location arrays.

## Prompt Examples

**Prompt:** 
```
Find the coordinates for 10 Downing St in London.
```

**Response:** 
```
| Location | Latitude | Longitude |
| :--- | :--- | :--- |
| 10 Downing St, London | 51.5033 | -0.1276

I've located the coordinates for the address provided. Would you like me to find nearby points of interest as well?
```

**Prompt:** 
```
What's near the Empire State Building?
```

**Response:** 
```
Here are some notable places near the Empire State Building:

*   **MoMA** (Museum of Modern Art)
*   **Summit One Vanderbilt**
*   **New York Public Library**

I can provide more specific details or filter these by a certain distance if you'd like.
```

**Prompt:** 
```
Check if these 5 addresses are in the US.
```

**Response:** 
```
I've checked the locations for you:

1. 1600 Pennsylvania Ave, Washington, DC - **USA**
2. 10 Downing St, London - **United Kingdom**
3. Eiffel Tower, Paris - **France**
4. Champs-Élysées, Paris - **France**
5. Sydney Opera House - **Australia**

Let me know if you need me to filter these results further.
```

## Capabilities

### Turn addresses into GPS coordinates
Convert human-readable street addresses into precise latitude and longitude points.

### Find street addresses from coordinates
Take a set of GPS points and retrieve the corresponding real-world street names and numbers.

### Provide real-time location suggestions
Offer instant place suggestions as users type into a search bar to improve UX.

### Filter results by country boundaries
Limit your search results to specific countries to avoid getting irrelevant international data.

### Search within a specific radius
Retrieve nearby points of interest that fall within a defined distance from a specific point.

### Extract detailed place properties
Pull rich schema properties and metadata for a specific location using its unique ID.

### Identify geometries in a bounding box
Find every location that falls inside a specific rectangular coordinate area.

## Use Cases

### Cleaning a messy CSV
A data analyst has 5,000 addresses with typos. They ask the agent to use structured_geocoding to clean the list and return a table of coordinates.

### Building a Near Me feature
A developer wants to show cafes. They ask the agent to use reverse_distance_limit to find spots within 2 miles of the user's current GPS.

### Mapping a city's parks
A planner needs to find all parks in a specific area. They ask the agent to use search_bounding_box to grab all POIs in a set of coordinates.

### Setting up a delivery zone
A logistics manager wants to know which countries a service covers. They use search_country_filter to see which ISO limits are active.

## Benefits

- Stop manually cleaning addresses by using structured_geocoding to isolate regions and terms automatically.
- Build faster search bars by using search_autocomplete to give users instant location suggestions.
- Validate your data's accuracy by using reverse_geocode to check if coordinates match the expected street names.
- Control your search area perfectly with search_bounding_box to keep results inside specific map rectangles.
- Save on API costs by using search_country_filter to drop international results you don't need.
- Improve user experience with search_focus_bias to make sure results are actually near where the user is looking.

## How It Works

The bottom line is that it turns your AI into a production-ready geospatial engine.

1. Connect your Pelias API key and base URL to your AI client configuration.
2. Describe the location task, like finding a city's coordinates or searching for nearby parks.
3. Receive structured JSON data with precise coordinates, bounding boxes, or place details.

## Frequently Asked Questions

**Can Pelias Geocoder help me clean a list of addresses?**
Yes, it can take a list of messy, human-entered addresses and return clean, structured coordinates and location data.

**How does Pelias Geocoder handle international locations?**
It supports global geocoding and can be filtered by specific country boundaries to ensure you only get the results you need.

**Can I use Pelias Geocoder for a "near me" search?**
Yes, it can find nearby points of interest within a specific radius from any given GPS coordinate.

**Does Pelias Geocoder support autocomplete for my search bar?**
It provides real-time location suggestions as users type, making it perfect for building interactive search features.

**How do I limit search results to a specific city?**
You can use bounding box logic or country filters to ensure your agent only returns results within your desired geographic area.

**Can Pelias Geocoder find coordinates from a street name?**
Yes, it can resolve street names and addresses into precise latitude and longitude coordinates for your maps.

**Can I use Pelias bounds configuring explicit extraction of local custom data stores?**
Yes. This configuration inherently parses dynamic host architecture. You explicitly bind the native Base URL to point strictly toward your configured self-hosted arrays or Pelias-compatible public limit providers natively globally.

**How explicitly strict are the parameter bounds when I invoke bounded reversed logistics natively?**
You map explicit limits using standard decimal notation gracefully parsing constraints natively: `lat=40.73` and `lon=-73.93`. The limits parse efficiently checking the closest explicit street JSON outputs securely returning structured bounded nodes.

**Is the structured Autocomplete log bound explicitly evaluating live typing constraints?**
Absolutely structurally globally bound. Command the `search_autocomplete` natively with partial strings (e.g., '100 Main S'), and the AI extracts arrays modeling how your specific UI limit bounds react dynamically effortlessly.