cortex
by rlaksana
Overview
AI-optimized knowledge management system providing advanced memory storage, multi-strategy semantic search, intelligent deduplication, and comprehensive monitoring for AI agent knowledge operations, including deep Z.AI integration.
Installation
node dist/index.jsEnvironment Variables
- OPENAI_API_KEY
- QDRANT_URL
- QDRANT_API_KEY
- ZAI_API_KEY
- NODE_ENV
- LOG_LEVEL
- MCP_API_KEY
- JWT_SECRET
- ENCRYPTION_KEY
- QDRANT_COLLECTION_NAME
- EMBEDDING_MODEL
- DEDUPE_SIMILARITY_THRESHOLD
- DEDUPE_MERGE_STRATEGY
- TTL_DEFAULT_DAYS
- MAX_MEMORY_MB
- HEALTH_ENDPOINT_API_KEY
Security Notes
The server implements robust security middleware including JWT authentication, API key validation, IP validation, rate limiting, CORS, Helmet for security headers, and input sanitization (SQL/XSS prevention). It leverages `process.env` for configuration and includes a `KeyVaultService` for sensitive key management. However, a critical vulnerability exists due to the explicit use of `new Function()` in `src/services/monitoring/runbook-integration-service.ts` to execute `scriptContent`. If 'runbook' definitions or `scriptContent` can be influenced by untrusted or even privileged user input without strict sandboxing, this constitutes an arbitrary code execution vulnerability. This severely undermines the claim of 'production readiness' as it provides a direct code injection vector.
Similar Servers
mcp-documentation-server
A local-first MCP server for document management, semantic search, and AI-powered document intelligence.
memorizer-v1
A .NET-based service for AI agents to store, retrieve, and search through long-term memories using vector embeddings, PostgreSQL (pgvector), and a Model Context Protocol (MCP) API, featuring versioning, relationships, and asynchronous chunking.
pluggedin-app
A testing environment for MCP (Model Context Protocol) servers, enabling interaction via a chat interface powered by Large Language Models (LLMs) and LangChain ReAct framework.
claude-context-enhanced
Provides semantic code search capabilities to AI coding assistants (like Claude Code) by indexing entire codebases into a vector database for deep contextual understanding, enhancing AI agents with relevant code context.