Synthesize GitHub Issues, HN and App Store reviews into ranked pain clusters. Pay-per-call x402.
Synthesize GitHub Issues, HN and App Store reviews into ranked pain clusters. Pay-per-call x402.
Valid MCP server (2 strong, 3 medium validity signals). 2 known CVEs in dependencies Package registry verified. Imported from the Official MCP Registry.
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Set these up before or after installing:
Environment variable: EVM_PRIVATE_KEY
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-sapph1re-feedback-synthesis-mcp": {
"env": {
"EVM_PRIVATE_KEY": "your-evm-private-key-here"
},
"args": [
"feedback-synthesis-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
Customer feedback intelligence for AI agents and developers. Synthesize GitHub Issues, Hacker News threads, and App Store reviews into ranked pain clusters with evidence links. Pay-per-call via x402 micropayments — no signup required.
Stop reading through hundreds of feedback items manually. Feedback Synthesis MCP collects from multiple sources, runs a multi-pass LLM pipeline, and returns ranked pain clusters with impact scores, evidence links, and suggested actions — machine-readable for agents, human-readable for founders.
Install:
pip install feedback-synthesis-mcp
Set your wallet key (any EVM wallet with USDC on Base mainnet):
export EVM_PRIVATE_KEY=your_private_key_here
Add to Claude Desktop — edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"feedback-synthesis-mcp": {
"command": "feedback-synthesis-mcp",
"env": {
"EVM_PRIVATE_KEY": "your_private_key_here"
}
}
}
}
Add to Cursor — edit .cursor/mcp.json in your project root:
{
"mcpServers": {
"feedback-synthesis-mcp": {
"command": "feedback-synthesis-mcp",
"env": {
"EVM_PRIVATE_KEY": "your_private_key_here"
}
}
}
}
Restart your client. You now have four customer intelligence tools available.
| Tool | What it does | Price |
|---|---|---|
synthesize_feedback | Multi-source synthesis → ranked pain clusters with evidence | $0.05/call |
get_pain_points | Quick single-source pain point extraction | $0.02/call |
search_feedback | Full-text search across cached feedback items | $0.01/call |
get_sentiment_trends | Time-series sentiment across sources | $0.03/call |
Supported sources: GitHub Issues, Hacker News, Apple App Store Reviews
synthesize_feedback(
sources=[
{"type": "github_issues", "target": "owner/my-repo", "labels": ["bug", "feature-request"]},
{"type": "hackernews", "target": "Show HN: MyProduct"}
],
since="2026-01-01T00:00:00Z"
)
Returns:
{
"job_id": "syn_abc123",
"status": "completed",
"summary": "Analyzed 347 feedback items from 2 sources. Found 6 pain clusters.",
"pain_clusters": [
{
"rank": 1,
"title": "Authentication flow breaks on mobile Safari",
"severity": "critical",
"frequency": 23,
"impact_score": 0.92,
"description": "Users report inability to complete OAuth login on iOS Safari. Affects onboarding conversion.",
"evidence": [
{
"source": "github",
"url": "https://github.com/owner/my-repo/issues/142",
"snippet": "Login fails silently on Safari 17.2+"
}
],
"suggested_actions": [
"Fix Safari WebAuthn polyfill (see issue #142)",
"Add fallback auth flow for mobile browsers"
]
}
]
}
get_pain_points(
source={"type": "github_issues", "target": "owner/my-repo", "labels": ["bug"]},
top_n=5
)
search_feedback(query="pricing too expensive", sources=["github_issues", "hackernews"])
get_sentiment_trends(
sources=[{"type": "appstore", "target": "com.example.myapp"}],
since="2025-10-01T00:00:00Z",
granularity="weekly"
)
This MCP uses x402 micropayments on Base mainnet (USDC). You need:
EVM_PRIVATE_KEYEach call costs $0.01–$0.05 USDC. Payments are made automatically — no subscriptions, no API keys.
No payment configured? The server returns a helpful error with setup instructions.
This package is a thin MCP client. All processing happens on the hosted backend:
Your Agent / Claude Desktop
│
▼
feedback-synthesis-mcp (this package)
- MCP tool definitions
- x402 payment signing
- Zero business logic
│ HTTPS + x402
▼
Hosted Backend (Railway)
- Multi-source data collection
- 3-stage LLM pipeline (Haiku × N + Sonnet × 1)
- SQLite caching + FTS search
- x402 payment verification
Server code is private (moat). Thin client is open source.
MIT
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