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Feedback Analyzer Ai Mcp

  • Updated June 15, 2026
  • CSOAI-ORG/feedback-analyzer-ai-mcp

feedback-analyzer-ai-mcp is an MCP server that lets your coding agent analyze and synthesize user feedback without leaving the dev environment.

About

feedback-analyzer-ai-mcp is an MCP server from MEOK AI Labs that lets developers run feedback analysis through Claude Code, Cursor, or Codex instead of manually tagging tickets, App Store reviews, and Discord threads. After launch, qualitative noise often outpaces what one-person teams can triage; this server exposes analyzer tooling over stdio so your agent can cluster complaints, praise, and feature asks while you draft changelog entries or support macros. It targets the Grow phase when lifecycle and support decisions determine whether early traction sticks. The integration is domain-agnostic—SaaS, content products, and agent-native apps all benefit if you already collect text feedback somewhere the agent can reach. Pair it with your existing datastore or paste workflows; it is an analysis lens, not a full helpdesk replacement.

  • MEOK AI Labs feedback-analyzer MCP for in-agent feedback review workflows
  • Stdio transport via PyPI package feedback-analyzer-ai-mcp (version 1.0.4)
  • GitHub source at CSOAI-ORG/feedback-analyzer-ai-mcp for inspection and forks
  • Fits post-launch iteration loops without exporting CSVs to a separate SaaS only
  • Works alongside analytics MCPs by adding qualitative signal on top of metrics

Feedback Analyzer Ai Mcp by the numbers

  • Data as of Jul 7, 2026 (Skillselion catalog sync)
terminal
claude mcp add feedback-analyzer-ai-mcp -- uvx feedback-analyzer-ai-mcp

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Packagefeedback-analyzer-ai-mcp
TransportSTDIO
AuthNone
Last updatedJune 15, 2026
RepositoryCSOAI-ORG/feedback-analyzer-ai-mcp

What it does

Turn scattered user feedback into themes and priorities your agent can act on while you improve retention and support.

Who is it for?

Shipped products collecting reviews, emails, or in-app comments where one developer owns product and support.

Skip if: Pre-launch ideas with no user signal yet, or teams that already run a dedicated VoC platform with automated pipelines.

What you get

After registration, your agent can summarize sentiment, themes, and follow-ups from feedback you supply, speeding support and iteration decisions.

  • Themed feedback summaries for weekly product reviews
  • Prioritized issue lists for changelog and support doc updates
  • Draft replies or FAQ bullets grounded in recurring user language

By the numbers

  • Server version 1.0.4 on MCP schema 2025-12-11
  • PyPI identifier feedback-analyzer-ai-mcp with stdio transport
  • Public repository: github.com/CSOAI-ORG/feedback-analyzer-ai-mcp
README.md

MCP Scorecard: 86/100

Feedback Analyzer Ai MCP

MEOK AI Labs EU AI Act License PyPI

Analyze customer feedback for sentiment, themes, and actionable insights

Analyze customer feedback for sentiment, themes, and actionable insights.


🚀 Quick Start

# Install via pip
pip install feedback_analyzer_ai_mcp

# Or install via Smithery
npx -y @smithery/cli@latest install feedback-analyzer-ai-mcp --client claude

✨ Features

  • MCP protocol compliant
  • Easy installation
  • Well-documented API
  • Production-ready
  • Active maintenance

📖 Documentation

🛡️ Compliance

This MCP server is built with EU AI Act compliance built-in:

  • ✅ Article 9 — Risk Management System
  • ✅ Article 13 — Transparency & Instructions for Use
  • ✅ Article 15 — Bias Detection & Testing
  • ✅ Article 26 — FRIA Support (where applicable)
  • ✅ Article 50 — AI Content Watermarking (where applicable)

Need help getting compliant? Book a free 15-min diagnostic →

🏢 Enterprise

Need custom development, SLA guarantees, or white-label deployment?

  • Pro: $99/mo — Full MCP suite + EU AI Act tracking
  • Enterprise: $499/mo — Custom dev + SLA + Dedicated support

View Pricing → | Contact Sales →

🤝 Part of the MEOK Ecosystem

This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.

Domain Purpose
councilof.ai EU AI Act compliance marketplace
safetyof.ai AI safety & monitoring
meok.ai Sovereign AI platform
cobolbridge.ai Legacy modernization

📜 License

MIT © CSOAI-ORG


Built with 💜 by MEOK AI Labs · UK Companies House 16939677

MIT © [MEOK AI Labs](https://meok.ai)

Pairs with MEOK Governance Suite

Build something that touches users? You need compliance. MEOK ships 38 governance MCPs that drop in alongside this tool — EU AI Act, DORA, NIS2, CRA, GDPR, ISO 42001, FDA SaMD, MDR, Basel, MiFID II, MiCA, COPPA, and more.

# One-shot install of the governance pack
npx meok-setup --pack governance

Free tier: 10 calls/day per MCP. Pro tier (£79/mo): unlimited + cryptographically signed compliance attestations your auditor verifies independently.

→ Full catalogue: councilof.ai/catalogue → MEOK AI Labs: meok.ai

💸 Try MEOK in 30 seconds — instant buy ladder

Tier Price What you get Stripe
Smoke test £1 Signed sample MCP-Hardening report + Article 50 PDF https://buy.stripe.com/aFa7sNcgAdQS0ZT1Uc8k91t
Quick Kit £9 EU AI Act Article 50 implementation guide (C2PA + EU-Icon) https://buy.stripe.com/aFa7sNcgAdQS0ZT1Uc8k91t
Founder Call £29 30-min 1-on-1 with the founder https://buy.stripe.com/aFa7sNcgAdQS0ZT1Uc8k91t

Refundable. UK Stripe — VAT-clean. Builds on the 81-MCP MEOK fleet. Verify any signed report at https://meok.ai/verify.

Configuration

Add to your claude_desktop_config.json (Claude Desktop) or your MCP client config:

{
  "mcpServers": {
    "feedback-analyzer-ai-mcp": {
      "command": "uvx",
      "args": ["feedback-analyzer-ai-mcp"]
    }
  }
}

Or: pip install feedback-analyzer-ai-mcp then run the feedback-analyzer-ai-mcp command (stdio transport).

Examples

Once configured, ask your assistant, for example:

  • "Use analyze_feedback to …"
  • "Use extract_themes to …"
  • "Use sentiment_trend to …"

Recommended MCP Servers

How it compares

In-agent feedback analysis MCP, not a ticketing system or survey collection product.

FAQ

Who is feedback-analyzer-ai-mcp for?

It is for SaaS and app developers who want MCP-driven feedback summarization inside Claude Code, Cursor, or similar agents.

When should I use feedback-analyzer-ai-mcp?

Use it in Grow when you are prioritizing bugs, docs gaps, and feature requests from real user text.

How do I add feedback-analyzer-ai-mcp to my agent?

Install feedback-analyzer-ai-mcp from PyPI (1.0.4), add a stdio MCP server block for io.github.CSOAI-ORG/feedback-analyzer-ai-mcp, and restart your agent.

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