Astro MCP Server

An MCP (Model Context Protocol) server that provides access to Astro ASO (App Store Optimization) data for LLMs.

Requirements

• Astro

• A tool with MCP support (Claude Desktop, Claude Code, ...)

Features

This MCP server provides the following tools for querying Astro's ASO database:

Available Tools

1. search_rankings - Search current keyword rankings for apps

   • Find how apps rank for specific keywords

   • Filter by app store (us, uk, etc.)

   • Filter by app name or app ID

2. get_historical_rankings - Get historical ranking data

   • Track ranking changes over time

   • Configurable time period (default: 30 days)

   • Filter by app and store

3. list_apps - List all tracked applications

   • Shows app names, IDs, platforms

   • Includes keyword count per app

4. get_app_keywords - Get all keywords for a specific app

   • Shows current and previous rankings

   • Includes difficulty and popularity scores

   • Shows ranking changes

   • Accepts app name or app ID

5. get_keyword_trends - Analyze ranking trends

   • Statistical analysis (avg, min, max, volatility)

   • Trend detection (improving/declining/stable)

   • Configurable periods (week/month/year/all)

6. compare_rankings - Compare rankings between dates

   • Find ranking changes between two specific dates

   • Calculate percentage changes

7. get_app_ratings - Get app rating history

   • Track rating changes over time

   • Shows user rating counts

   • Accepts app name or app ID

8. get_keyword_competitors - Get real App Store competitors for keywords

   • Shows actual competitor apps from App Store data with app categories

   • Rankings based on real App Store search results

   • Multi-store support with automatic data aggregation

   • Configurable limit for number of competitors returned

9. get_keyword_recommendations - Get keyword recommendations

   • Suggests related keywords based on existing tracking data

   • Helps discover new keyword opportunities

   • Fuzzy matching for broader keyword discovery

10. analyze_competitive_landscape - Comprehensive competitive analysis

    • Identifies top competitors across all tracked keywords with app categories

    • Calculates market share metrics (top 10/25/50 rankings)

    • Shows competitor dominance scores and shared keywords

    • Assesses competitive intensity levels

    • Configurable limit for number of competitors returned

11. calculate_keyword_opportunity - Find keyword opportunities

    • Identifies high-opportunity keywords with low competition

    • Combines popularity, difficulty, and competition metrics

    • Configurable thresholds for targeted opportunity discovery

    • Provides reasoning for each opportunity score

12. detect_ranking_anomalies - Detect unusual ranking changes

    • Identifies sudden ranking drops, rises, and volatility spikes

    • Provides context about timing and previous rankings

    • Categorizes anomaly severity (low/medium/high/critical)

    • Includes interpretation of ranking changes

13. predict_ranking_trends - Predict future ranking movements

    • Uses linear regression to forecast ranking trajectories

    • Provides confidence scores and trend directions

    • Estimates future ranking positions based on historical data

    • Shows methodology and data points used for predictions

14. find_low_competition_keywords - Discover underutilized keywords

    • Finds keywords with low competition scores

    • Balances difficulty vs. popularity for optimal targeting

    • Helps identify niche market opportunities

    • Configurable parameters for precise filtering

Installation

Prerequisites

• Astro app must be installed on your Mac with data in its database

• Node.js 18+ required

  # Check your Node version node --version

Usage with Claude

Claude Code (Recommended)

The easiest way to use this MCP server is with Claude Code:

Claude Desktop

Add the following to your Claude Desktop configuration:

For NPM installation:

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

For local/source installation:

First build the project:

Then add to Claude Desktop config:

Running Standalone

You can also run the server standalone for testing:

Using with MCP Inspector

Test the server using the MCP Inspector:

Example Queries

Once connected to Claude (via Claude Code or Claude Desktop), you can ask questions like:

Basic Queries:

• "Use Astro MCP to show the current rankings for the keyword 'productivity' in the US store"

• "Use Astro MCP to show me the ranking trends for 'task manager' over the last month"

• "Use Astro MCP to list all the apps being tracked"

• "Use Astro MCP to show what keywords the app 'Things 3' ranks for"

• "Use Astro MCP to compare rankings for 'notes' between last week and today"

• "Use Astro MCP to show me the rating history for app ID 1234567890"

Advanced Competitive Intelligence:

• "Use Astro MCP to show me the real App Store competitors for the keyword 'meditation' with their categories"

• "Use Astro MCP to analyze the competitive landscape for my app in the productivity space, showing top 15 competitors"

• "Use Astro MCP to find keyword opportunities with low competition and high popularity"

• "Use Astro MCP to detect any ranking anomalies in my app's performance this week"

• "Use Astro MCP to predict where my 'todo app' keyword will rank next month"

• "Use Astro MCP to find low-competition keywords I should target for my wellness app"

• "Use Astro MCP to get keyword recommendations based on my current 'fitness' keyword"

Database Requirements

The server requires read access to Astro's SQLite database, typically located at:

Make sure Astro has been run at least once and has collected some data before using this server.

Technical Details

• Runtime: Node.js 18+

• Database: SQLite via sql.js (JavaScript implementation, no native compilation required)

• Database Loading: Automatically detects and reloads database changes, including WAL mode support with checkpoint forcing

• Protocol: MCP (Model Context Protocol) via stdio

• TypeScript: Compiled to JavaScript for distribution

• Date Handling: Converts Core Data timestamps to ISO format

• App Identification: Supports both app names (partial matching) and app IDs (exact matching)

• WAL Mode Support: Automatically handles Write-Ahead Logging mode databases by forcing checkpoints to merge recent changes

Database Schema

The server reads from these main tables in Astro's database:

• ZAPPLICATION - App information

• ZKEYWORD - Keywords and current rankings

• ZDATAPOINT - Historical ranking data points

• ZBINARYDATA - Real App Store competitor data (JSON format)

• ZRATING - App ratings

• ZRATINGDATAPOINT - Historical rating data

Development

Project Structure

Building from Source

1. Clone the repository

2. Install dependencies: npm install

3. Build the project: npm run build

4. Run in development mode: npm run dev

Publishing to NPM

1. Update version in package.json

2. Update author and repository URLs in package.json

3. Run: npm publish (automatically builds via prepublishOnly)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT - See LICENSE file for details

Troubleshooting

Common Issues

1. "Database not found" error

   • Ensure Astro is installed and has been run at least once

   • Check that the database path exists

2. "Permission denied" error

   • The server needs read access to Astro's database

   • Check file permissions on the SQLite database

3. Node.js compatibility

   • Ensure you're using Node.js 18 or higher

   • The server uses sql.js (pure JavaScript), so no native module compilation is required

   • This eliminates NODE_MODULE_VERSION errors that were common with better-sqlite3

4. No data returned or stale data

   • Ensure Astro has collected keyword tracking data

   • Check that you're using the correct app names or IDs

   • Verify the store parameter (default is 'us')

   • The server automatically reloads the database when changes are detected

   • For WAL mode databases, recent changes are merged automatically via checkpoints

Support

For issues or questions, please open an issue on GitHub.

This project was vibecoded with ❤️ by