claude-mapsdb

avocade/claude-mapsdb

3.2

If you are the rightful owner of claude-mapsdb and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

This project allows you to query your saved Google Maps places using natural language through Claude Desktop/Code, leveraging an SQLite database and MCP server.

Places Database

Google Maps saved places → SQLite → Claude MCP Server

Query your saved places with natural language through Claude Desktop/Code.

Quick Start

bb setup                      # Install dependencies
cp *.csv data/               # Add your Google Maps exports
bb places:import             # Import to SQLite
bb index:fts                 # Build search index
bb mcp:config                # Get Claude config

See for complete documentation.

What You Get

  • SQLite database with full schema (name, coords, categories, ratings, notes)
  • FTS5 search for instant text queries
  • Spatial queries (find places within X km)
  • MCP server for Claude integration
  • Free geocoding via Nominatim/OSM
  • Deduplication and smart updates

Usage

Command Line

bb query:lists               # Show all your lists
bb query:near 59.3 18.1 5   # Places within 5km
bb places:stats              # Database stats

Via Claude

Once configured:

  • "Show restaurants in Stockholm"
  • "Find hiking places within 10km of Abisko"
  • "What places do I have in Japan?"

Architecture

CSV → import_places.py → SQLite (FTS5, spatial index)
                            ↓
                    places_mcp_server.py ← Claude Desktop/Code

Tasks

Run bb tasks to see all available commands.

Key tasks:

  • places:import - Initial import
  • places:update - Merge new exports
  • geo:enrich - Add missing coordinates
  • index:fts - Build search index
  • mcp:config - Get Claude config

Files

  • bb.edn - Task definitions (fully documented)
  • scripts/*.py - Import, geocoding, indexing, MCP server
  • data/places.db - Your SQLite database
  • CLAUDE.md - Full documentation

Requirements

  • Python 3.8+
  • Babashka 1.3.0+
  • SQLite 3.35+

Install deps: bb setup

Cost

  • Import/search: $0 (local)
  • Geocoding: $0 (Nominatim)
  • Embeddings: ~$0.50 for 24k places (optional)

Pattern Inspiration

Adapted from Email Archive MCP

🔮 Predictions

You'll want:

  • Spatial queries (works now via Haversine, faster with SpatiaLite)
  • Semantic search ($0.50 for embeddings: bb cost:embeddings)
  • Regular updates from new Google exports: bb places:update

The geocoding is your bottleneck—8,560 places @ 1 req/sec = 2.4 hours. Run overnight or accept current 46% coverage.

Pattern proven via your email archive. Same architecture, different domain.

Your maps. Your data. Your queries.