SignalMiner

Overview

SignalMiner is an AI-powered Telegram community intelligence agent that automatically monitors your community channels, extracts actionable feedback, and delivers weekly insights. Designed for founders and community managers, it transforms buried Telegram conversations into structured product intelligence—classifying messages by type, identifying trends, and surfacing the most impactful user signals without manual effort.

How It Works

1. Get Chat (Telegram) — Retrieves metadata and member count for each monitored community channel to establish baseline community health.
2. Track Member Growth (Telegram) — Monitors week-over-week member count changes to correlate community growth with feedback patterns.
3. Collect Recent Messages (Telegram) — Extracts all messages from the past 7 days across monitored channels for analysis.
4. Classify Messages (Claude Haiku via mcp-claude) — Uses fast, cost-efficient AI classification to tag each message as Bug Report, Feature Request, Positive Feedback, Question, Churn Signal, or Noise.
5. Extract Top Insights (Claude Opus via mcp-claude) — Analyzes classified messages to identify the most-requested features, recurring bugs, common questions, and memorable user quotes.
6. Create Linear Issues (mcp-linear) — Automatically generates Linear issues for each actionable bug and feature request, pre-populated with community context and user quotes.
7. Log Intelligence Report (Notion via mcp-notion) — Creates a weekly database entry documenting message volume, sentiment breakdown, top issues, and trending topics for historical tracking.
8. Post Weekly Brief (Slack via mcp-slack) — Sends a curated community intelligence summary to your #product channel, highlighting the top 3 user signals and linking directly to created Linear issues.

Key Features

• Automated Message Classification — Instantly categorizes Telegram feedback by sentiment and type using advanced AI, eliminating manual sorting and ensuring no signal is missed.
• Trend Detection & Ranking — Identifies the most-requested features and recurring bugs by frequency, surfacing what your community actually wants most.
• Seamless Linear Integration — Automatically creates prioritized issues from community feedback, complete with user context, so your product team can act immediately.
• Persistent Intelligence Database — Weekly reports logged to Notion create a searchable, historical record of community sentiment and product demand over time.
• Daily-Ready Insights — Slack digest delivers the top 3 user signals every week, keeping your product team in sync without context-switching.

Use Cases

• Early-Stage Startups — Founders can identify the most-requested features and critical bugs directly from their community without hiring a customer research analyst.
• Product Teams — Monitor feature request velocity and sentiment trends week-over-week to validate roadmap priorities against real user demand.
• Community-Driven Products — Projects like open-source tools, SaaS platforms, or Discord/Telegram communities can surface churn signals early and respond to at-risk users proactively.
• Investor Relations — Demonstrate user-driven product development and community growth metrics to investors by sharing aggregated weekly intelligence reports.