# AllTrails MCP Server (`axlymxp/alltrails-mcp-server`) Actor

MCP server + scraper for AllTrails. Search hiking trails, fetch full details, reviews and weather live from Claude, ChatGPT, Cursor and other AI agents — or run it as a classic scraper.

- **URL**: https://apify.com/axlymxp/alltrails-mcp-server.md
- **Developed by:** [axly](https://apify.com/axlymxp) (community)
- **Categories:** Travel, Developer tools, Automation
- **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## AllTrails MCP Server

Give your AI assistant live access to **AllTrails** hiking data. This actor runs
as a **Model Context Protocol (MCP) server** so agents like **Claude, ChatGPT,
Cursor, and n8n** can search trails, pull full trail details, read reviews, check
weather, and autocomplete places — on demand. It also runs as a **classic
scraper** that pushes trail rows to a dataset.

### Why MCP

Instead of pre-scraping and storing data, your agent queries AllTrails live while
it reasons — perfect for trip-planning assistants, outdoor chatbots, and research
copilots. No other AllTrails MCP server exists on the Store.

### Tools exposed

| Tool                | What it does                                                                                     |
| ------------------- | ------------------------------------------------------------------------------------------------ |
| `search_trails`     | Search trails by place name or lat/lng — length, elevation, difficulty, GPS, rating, activities  |
| `get_trail_details` | Full description, highlights, tips, getting-there, parking, points of interest, rating breakdown |
| `get_trail_reviews` | Recent user reviews for a trail (sortable)                                                       |
| `get_trail_weather` | Multi-day weather forecast for a trail                                                           |
| `suggest_places`    | Autocomplete places, parks and trails for a partial query                                        |

### Who it's for

- **AI app builders** — add trail search + detail to an assistant with a few MCP tools.
- **Trip-planning bots** — combine `search_trails` + `get_trail_weather` for
  weather-aware suggestions.
- **Outdoor content copilots** — pull descriptions and reviews on demand.

### Connect your agent

Run the actor in **Standby mode** and point your MCP client at the server URL:

```
https://<your-actor-standby-url>/mcp
```

Example (Claude Desktop `mcp` config):

```json
{
    "mcpServers": {
        "alltrails": {
            "url": "https://<your-actor-standby-url>/mcp",
            "headers": { "Authorization": "Bearer <APIFY_TOKEN>" }
        }
    }
}
```

Then ask: *"Find moderate trails near Lake Tahoe with great views, and check the
weather for the top one."*

### Classic scraper mode

Run it normally with an input (place, coordinates, filters) and it pushes trail
rows to the dataset — same fields as the AllTrails Trail Scraper.

#### Output fields (dataset mode)

| Field                                    | Type       | Description            |
| ---------------------------------------- | ---------- | ---------------------- |
| `id`                                     | int        | Trail ID               |
| `name`                                   | string     | Trail name             |
| `url`                                    | string     | AllTrails URL          |
| `latitude` / `longitude`                 | number     | Trailhead GPS          |
| `areaName` / `stateName` / `countryName` | string     | Location               |
| `lengthMiles`                            | number     | Length                 |
| `elevationGainMeters`                    | number     | Elevation gain         |
| `difficulty`                             | string     | easy / moderate / hard |
| `avgRating` / `numReviews`               | number/int | Community rating       |
| `activities` / `features`                | array      | Tags                   |
| `scrapedAt`                              | string     | Timestamp              |

### Example input (classic run)

```json
{ "query": "Yosemite National Park", "maxItems": 10, "sort": "most_popular" }
```

### FAQ

**Do I need a login or proxy?** No — the actor handles AllTrails' anti-bot
automatically and needs no account.

**How fresh is the data?** Every tool call fetches live data.

**What data source is used?** AllTrails' public mobile API — the same data the
app shows.

**Is scraping legal?** You are responsible for complying with AllTrails' terms
and applicable laws. Use the data responsibly.

# Actor input Schema

## `query` (type: `string`):

Location to search around, e.g. "Yosemite National Park". Used only for a classic run.

## `latitude` (type: `number`):

Search-center latitude (overrides query with longitude).

## `longitude` (type: `number`):

Search-center longitude (overrides query with latitude).

## `maxItems` (type: `integer`):

Trails to return in a classic run.

## `sort` (type: `string`):

How to order results.

## `difficulty` (type: `array`):

Only include trails of these difficulties.

## `minRating` (type: `number`):

Only include trails rated >= this (0–5).

## Actor input object example

```json
{
  "query": "Yosemite National Park",
  "maxItems": 30,
  "sort": "best_match",
  "difficulty": []
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "Yosemite National Park"
};

// Run the Actor and wait for it to finish
const run = await client.actor("axlymxp/alltrails-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "query": "Yosemite National Park" }

# Run the Actor and wait for it to finish
run = client.actor("axlymxp/alltrails-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "Yosemite National Park"
}' |
apify call axlymxp/alltrails-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=axlymxp/alltrails-mcp-server",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/b1egmpepxUh0kgJOh/builds/0mNb2UDj7hhugZdoE/openapi.json