Model Context Protocol (MCP) server for AppReviewFetch. Enables AI assistants like GitHub Copilot and Claude to access app review data from App Store Connect and Google Play. Install globally with: dotnet tool install -g AppReviewFetch.Mcp
$ dotnet add package AppReviewFetch.McpA Model Context Protocol (MCP) server that provides AI assistants with access to App Store Connect and Google Play review data. This enables AI tools like GitHub Copilot, Claude, and other MCP clients to analyze app reviews, monitor sentiment, and help with customer feedback management.
Model Context Protocol is a standardized protocol that allows AI assistants to securely access external data sources and tools. This MCP server exposes your app review data to compatible AI clients.
Install as a global .NET tool:
dotnet tool install -g AppReviewFetch.Mcp
# Install CLI if you haven't already
dotnet tool install -g AppReviewFetch.Cli
# Run setup
arfetch setup
.p8 file and note your Key ID and Issuer IDarfetch setup to configure credentials interactivelyCreate or edit .vscode/mcp.json in your workspace (or user settings):
{
"inputs": [],
"servers": {
"appreviewfetch": {
"type": "stdio",
"command": "arfetch-mcp"
}
}
}
Restart VS Code or reload the MCP servers, then toggle Agent mode (@ icon) in GitHub Copilot Chat to see the AppReviewFetch tools.
Edit your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"appreviewfetch": {
"command": "arfetch-mcp"
}
}
}
Add to your MCP settings:
{
"mcpServers": {
"appreviewfetch": {
"command": "arfetch-mcp"
}
}
}
The server exposes three powerful tools for AI assistants:
Lists all apps accessible through your App Store Connect account.
Returns:
Example AI query: "Show me all my apps"
Fetches reviews for a specific app with advanced filtering and pagination.
Parameters:
appId (required) - App Store Connect app IDsortOrder (optional) - NewestFirst (default), OldestFirst, HighestRatingFirst, LowestRatingFirst, MostHelpfulcountry (optional) - ISO 3166-1 alpha-2 code (e.g., "US", "GB", "JP")limit (optional) - Reviews per page (1-200, default: 50)cursor (optional) - Pagination cursor from previous responseReturns:
Example AI queries:
Performs comprehensive statistical analysis of app reviews.
Parameters:
appId (required) - App Store Connect app IDcountry (optional) - Filter by territorymaxReviews (optional) - Maximum reviews to analyze (default: 500)Returns:
Example AI queries:
You: @appreviewfetch List all my apps
Copilot: [Uses ListApps tool]
I found 3 apps:
1. MyAwesomeApp (ID: 123456789)
2. CoolTool (ID: 987654321)
3. BestApp (ID: 555555555)
You: Show me the latest negative reviews for MyAwesomeApp
Copilot: [Uses FetchReviews with sortOrder=LowestRatingFirst]
Here are the recent 1-2 star reviews...
[Analysis of common issues]
You: Analyze all reviews and give me a summary
Copilot: [Uses AnalyzeReviews]
Based on 342 reviews:
- Average rating: 4.3/5
- 68% are 5-star reviews
- Developer response rate: 45%
- Recent trend: Rating improving (+0.3 in last 30 days)
[Detailed insights...]
You: Can you check my App Store reviews and tell me what users are complaining about?
Claude: I'll use the AppReviewFetch MCP server to analyze your reviews.
[Uses ListApps to find your apps]
[Uses AnalyzeReviews to get insights]
[Provides detailed analysis with quotes from actual reviews]
# Install MCP Inspector (Node.js required)
npm install -g @modelcontextprotocol/inspector
# Test your server
mcp-inspector dotnet run --project /path/to/AppReviewFetchMcp.csproj
To debug the MCP server in VS Code:
.vscode/launch.json:{
"version": "0.2.0",
"configurations": [
{
"name": ".NET Core Attach",
"type": "coreclr",
"request": "attach",
"processName": "AppReviewFetchMcp"
}
]
}
All logs are sent to stderr to keep stdout clean for MCP protocol communication. Check your MCP client's logs:
~/Library/Logs/Claude/mcp*.log (macOS)The MCP server implements smart pagination strategies:
maxReviews limitnextCursor for manual pagination controlTips for AI prompts:
Contributions welcome at github.com/praeclarum/AppReviewFetch
MIT License - Copyright © 2026 praeclarum