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MegaMind

by oluwaeinstein007

Overview

A content ingestion and processing system for AI applications, capable of crawling web pages, parsing documents, chunking text, generating LLM embeddings, and storing data for semantic search.

Installation

Run Command
node dist/index.js

Environment Variables

  • LLM_PROVIDER
  • LLM_API_KEY
  • OPENAI_API_KEY
  • GOOGLE_API_KEY
  • GEMINI_EMBEDDING_MODEL
  • EMBEDDING_VECTOR_SIZE
  • QDRANT_HOST
  • QDRANT_KEY
  • QDRANT_ENABLED
  • DATABASE_URL
  • OPENWEATHER_API_KEY
  • VISA_API_KEY
  • IMMIGRATION_API_KEY

Security Notes

CRITICAL: The MCP server exposes tools like `INGEST_URL_TOOL` and `INGEST_FILE_TOOL` that accept arbitrary URLs for web crawling and arbitrary file paths for ingestion directly from the MCP client. This creates severe security vulnerabilities: 1. Server-Side Request Forgery (SSRF): An attacker could use `INGEST_URL_TOOL` to force the server to make requests to internal network resources, potentially disclosing sensitive information or exploiting internal services. 2. Local File Inclusion/Disclosure: An attacker could use `INGEST_FILE_TOOL` with paths like `/etc/passwd` or `../../.env` to read and ingest sensitive files from the server's filesystem. These tools lack explicit input validation or sanitization within the provided code, making them highly dangerous if exposed to untrusted input. The `transportType: 'stdio'` might mitigate direct network exposure, but a compromised MCP client or malicious input via the stdio channel still poses these risks.

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Stats

Interest Score0
Security Score1
Cost ClassMedium
Avg Tokens5120
Stars0
Forks0
Last Update2025-12-11

Tags

Web CrawlingDocument ParsingLLM EmbeddingsVector SearchAI Data Pipeline