Server data from the Official MCP Registry
Observatory of public media reception: classify YouTube comments for mood, support and controversy.
About
Observatory of public media reception: classify YouTube comments for mood, support and controversy.
Remote endpoints: streamable-http: https://pjq.life/mcp/
Security Report
PJQ is a media reception analysis platform with a React web client and MCP server integration. The codebase shows generally sound architecture with appropriate separation of concerns. No critical vulnerabilities or malicious patterns detected. Minor code quality issues around error handling and input validation in the i18n system are present but do not indicate security risk. Permissions are reasonable for a Developer Tools category server that integrates with external APIs. Supply chain analysis found 5 known vulnerabilities in dependencies (0 critical, 1 high severity).
3 files analyzed · 9 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
PJQ — Public Judgment Quotient
A seismograph for public opinion. PJQ measures how an audience actually received a piece of media — separating genuine opinion from fan noise, bots, and self-promoters.
Live: pjq.life · License: Apache-2.0
What this is
PJQ takes the URL of a piece of content (YouTube today; Reddit, Telegram, and
News next), samples the comments under it, and classifies every comment against
a 7-category stance rubric. The output is a verdict: a numeric reception
score (mood) plus a structured breakdown — how many people substantively
agreed, how many pushed back, how many stayed neutral, and how much noise is
drowning the signal.
Think of it as an observatory of media reception, exposed over two transports on one core:
- a REST API (
/api/v1/*) for analytics automation, and - an MCP server (
/mcp/) so AI agents (Claude Desktop and friends) can run analyses and read verdicts directly inside a chat.
What's in this repository
This repo is the open client + specification of PJQ. The hosted analysis engine (sampling, classification, QA, the ONNX stance model and the prompt internals) stays closed — it is the product's moat. What's open here is everything you need to use, integrate with, and understand PJQ:
web/ — the full web client (React + TypeScript + Vite SPA, 5 languages)
spec/ — the conceptual specification
├── CONCEPT.md what PJQ is and why
├── RUBRIC.md the 7-category stance rubric (definitions)
├── domains.yaml the 11-domain content taxonomy
├── FEATURED.md the open, automatic showcase-ranking formula
└── verdict-schema.md the shape of a verdict (API output)
docs/ — integration reference
├── api-reference.md REST API surface
├── mcp-reference.md MCP tools and schemas
└── user-guide/ end-user guide (EN + RU)
The 7-category rubric (in one breath)
Every comment gets exactly one of: SUP (substantive support), AGA (substantive against), NEU (neutral), OFF (off-topic), THIN (thin positive — praise without an argument), SUS (inorganic — bot / paid / coordinated), AGN (own agenda — the comment is a vehicle for the author's external goal).
Reporting rule: opinion metrics (mood, support) are computed strictly
from SUP / AGA / NEU. THIN / OFF / SUS / AGN are counted separately and never
inflate support percentages. See spec/RUBRIC.md.
Running the web client
The client is a standard Vite SPA. By default it talks to the hosted backend at
pjq.life (same-origin in production).
cd web
npm install
npm run dev # dev server with hot reload
npm run build # production build (with build-time SEO prerender) -> dist/
To point the client at a different backend, copy web/.env.example and set
VITE_API_BASE.
Integrating
- REST API — get an API key from the Cabinet on pjq.life,
then see
docs/api-reference.md. Read-only tools cost no credits; a full analysis costs one credit. - MCP — point an MCP-capable client at
https://pjq.life/mcp/and seedocs/mcp-reference.mdfor the exported tools.
Comment raw texts are never returned over the API — only aggregates, percentages, and a small set of representative exemplars, per PJQ's privacy policy.
Status
PJQ is live and in active development. The roadmap is public at pjq.life/flightlog. This repository tracks the client and the spec; engine changes ship to the hosted service.
License
Copyright 2026 PJQ (github.com/Makaric). Licensed under the Apache License,
Version 2.0 — see LICENSE.
Русская версия: README_RU.md.
Reviews
No reviews yet
Be the first to review this server!
More Developer Tools MCP Servers
Git
Freeby Modelcontextprotocol · Developer Tools
Read, search, and manipulate Git repositories programmatically
Fetch
Freeby Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
Toleno
Freeby Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
mcp-creator-python
Freeby mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.
MCP Marketplace
Freeby mcp-marketplace · Developer Tools
Search and install MCP servers from inside your AI client.
MarkItDown
Freeby Microsoft · Content & Media
Convert files (PDF, Word, Excel, images, audio) to Markdown for LLM consumption
