In-depth architectural comparison of the Memora and Memex MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Memora
Knowledge & Memory · Local stdio
Quality: 53/100 (Good) | Auth: API Key required
Memex
Knowledge & Memory · Local stdio
Quality: 43/100 (Fair) | Auth: No auth required
Verdict Summary: Choose Memora if you need specialized Knowledge & Memory tools running via a local process. Choose Memex if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Memora when:
You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: MEMORA_DB_PATH, MEMORA_STORAGE_URI, CLOUDFLARE_API_TOKEN, AWS_PROFILE, AWS_ENDPOINT_URL, MEMORA_CLOUD_ENCRYPT, MEMORA_ALLOW_ANY_TAG, MEMORA_GRAPH_PORT.
Primary tools included: Persistent storage with SQLite or cloud sync (S3, R2, D1), Hierarchical memory organization with sections and subsections, Semantic search using TF-IDF, sentence-transformers, and OpenAI embeddings.
Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.
Production-grade persistent memory service for AI agents. Semantic search with recency decay (configurable α blend), local ONNX embeddings (zero API cost), background memory summarisation, and Prometheus/Grafana observability. docker compose up — no cloud dependencies.
Category & Scope
Tools & Capabilities Breakdown
Memora Tools (6)
Persistent storage with SQLite or cloud sync (S3, R2, D1)
Hierarchical memory organization with sections and subsections
Semantic search using TF-IDF, sentence-transformers, and OpenAI embeddings
Knowledge graph visualization with Mermaid and live graph server
Memory linking with typed edges and AI-powered deduplication
RAG-powered chat interface for memory querying and updates
Memex Tools (6)
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Memora is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Memex belongs to Knowledge & Memory using local stdio subprocess. Select Memora when you need capabilities focused on knowledge & memory and Memex when you require tools for knowledge & memory.
You have access to required keys: DB_MAX_POOL_SIZE.
Primary tools included: Semantic vector search with recency decay re-ranking, Local ONNX embedding model (BAAI/bge-small-en-v1.5) for zero API cost, PostgreSQL 16 with pgvector and ivfflat index for efficient vector queries.