Gogo Backend MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
python -m pip install -r requirements.txt
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add -e "DATABASE_URL=${DATABASE_URL}" gogo-backend -- node "<FULL_PATH_TO_GOGO_BACKEND_MCP6>/dist/index.js"

Replace <FULL_PATH_TO_GOGO_BACKEND_MCP6>/dist/index.js with the actual folder you prepared in step 1.

Required:DATABASE_URL+ 1 optional
README.md

A FastMCP-powered server for accessing curated travel spot data.

gogo-backend-mcp

A lightweight MCP-powered backend for serving curated travel spots straight from model.spot. The FastMCP server in trip.py exposes tools that let any compatible client request the latest main attractions, supporting sites, and the top ten most popular destinations.

Features

  • major_views, sub_views, and top_10_spots tools implemented via FastMCP.
  • SQLAlchemy ORM mapped through model/spot.py with GeoAlchemy spatial support.
  • Environment-driven configuration with .env plus sensible defaults in util/database.py.

Requirements

python -m pip install -r requirements.txt

Environment

Copy .env.example (if you create one) or create a .env file with at least:

DATABASE_URL=postgresql+psycopg://user:password@localhost/spot_db
LOG_LEVEL=INFO

util/database.py will fall back to postgresql+psycopg://postgres:password@localhost/spot_db when nothing is provided.

Database

  • The app expects a PostgreSQL database with a public.spot table matching model.spot.Spot.
  • The table requires the PostGIS extension for the location geometry column.
  • Apply your own migrations or schema creation outside this service; SQLAlchemy will not auto-create tables here.

Running locally

python trip.py

The MCP server listens on stdio and exposes three async tools:

  1. major_views – active spots with popularity > 3000.
  2. sub_views – active spots with 1 < popularity < 3000.
  3. top_10_spots – ten most popular active spots.

Each tool returns JSON data from the respective helper in src/action.py.

Logging

util/logging_setup.py configures a single console handler; change LOG_LEVEL or wrap calls with your own handlers if you need file logging.

MCP Setup

This project uses FastMCP to create an MCP server. The server exposes three tools that clients can call to retrieve travel spot data.

{
    "servers": {
        "trip-mcp": {
            "command": "uv",
            "args": [
                "--directory",
                "/{Project Parent Location}",
                "run",
                "trip.py"
            ],
            "env": {
            }
        }
        // add your MCP stdio servers configuration here
        // example:
        // "my-mcp-server": {
        //     "type": "stdio",
        //     "command": "my-command",
        //     "args": [],
        //     "env": {
        //         "TOKEN": "my_token"
        //     }
        // }
    }
}

# gogo-backend-mcp6

Tools (3)

major_viewsRetrieves active travel spots with popularity greater than 3000.
sub_viewsRetrieves active travel spots with popularity between 1 and 3000.
top_10_spotsRetrieves the ten most popular active travel spots.

Environment Variables

DATABASE_URLrequiredPostgreSQL connection string for the spot database.
LOG_LEVELLogging level for the application (e.g., INFO).

Configuration

claude_desktop_config.json
{"servers": {"trip-mcp": {"command": "uv", "args": ["--directory", "/{Project Parent Location}", "run", "trip.py"]}}}

Try it

Show me the top 10 most popular travel destinations currently in the database.
List all major attractions with high popularity scores.
Find supporting travel sites that have moderate popularity.
What are the most visited spots available in the travel database?

Frequently Asked Questions

What are the key features of Gogo Backend?

Exposes travel spot data via FastMCP tools. Integrates with PostgreSQL using SQLAlchemy ORM. Supports spatial queries via PostGIS. Provides filtered access to travel spots based on popularity metrics.

What can I use Gogo Backend for?

Querying popular travel destinations for a travel planning application. Retrieving curated lists of major attractions for content generation. Filtering travel spots by popularity levels for data analysis. Integrating spatial travel data into AI-assisted trip planning workflows.

How do I install Gogo Backend?

Install Gogo Backend by running: python -m pip install -r requirements.txt

What MCP clients work with Gogo Backend?

Gogo Backend works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep Gogo Backend docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare