TruthLens: Misinformation Surveillance Platform MCP Server

@NemroNeno

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Basic information

About TruthLens: Misinformation Surveillance Platform MCP Server

No overview available yet

#truthlens#misinformation#surveillance#fact-checking

TruthLens: Misinformation Surveillance Platform MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp_server_TruthAnalyzer": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

TruthLens: Misinformation Surveillance Platform MCP Server tools

Tool list not available yet

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Overview

What is TruthLens: Misinformation Surveillance Platform?

TruthLens is a Model Context Protocol (MCP) server that provides AI assistants with tools to detect, analyze, and verify potential misinformation. Built with Python and the MCP framework, it enables automated fact-checking and misinformation monitoring capabilities.

How to use TruthLens: Misinformation Surveillance Platform?

Install dependencies and set API keys in a .env file, then run python run_server.py. Invoke MCP endpoints such as ingest_url, extract_claims, verify_claim, search_news, analyze_source, get_trending_info, and setup_monitor.

Key features of TruthLens: Misinformation Surveillance Platform?

Ingests web content from URLs and news sources
Extracts factual claims using pattern matching or Gemini AI
Verifies claims against multiple external knowledge sources
Monitors news and analyzes misinformation trends
Provides confidence scores and evidence for each claim

Use cases of TruthLens: Misinformation Surveillance Platform?

Automated fact-checking for news articles and social media posts
Monitoring and analyzing trending misinformation by topic
Verifying the veracity of claims for journalists and researchers
Analyzing source credibility before content dissemination

Frequently asked questions

What are the runtime dependencies for TruthLens: Misinformation Surveillance Platform?

Python 3.10 or higher and at minimum a Google Gemini API key for AI-powered analysis.

Where does TruthLens: Misinformation Surveillance Platform store data?

The current implementation uses in-memory storage and is not suitable for production.

What are the limitations of TruthLens: Misinformation Surveillance Platform?

Pattern matching fallback has limited accuracy compared to AI-powered analysis, and web scraping may be subject to rate limits and terms of service restrictions.

What external APIs does TruthLens: Misinformation Surveillance Platform require?

The Google Gemini API is required; NewsAPI and Reddit API are optional.

How does TruthLens: Misinformation Surveillance Platform handle missing API keys?

If API keys are missing, the system falls back to pattern

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