Rag Kb vs Memora — MCP Server Comparison | AllMCPs
Side-by-Side Model Context Protocol Comparison
Rag Kb vs Memora
In-depth architectural comparison of the Rag Kb and Memora 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
Rag Kb
Knowledge & Memory · Local stdio
Quality: 45/100 (Fair) | Auth: No auth required
Memora
Knowledge & Memory · Local stdio
Quality: 56/100 (Good) | Auth: API Key required
Verdict Summary: Choose Rag Kb if you need specialized Knowledge & Memory tools running via a local process. Choose Memora 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 Rag Kb when:
You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
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.
Local-first agent memory & knowledge service with hybrid retrieval (BGE-M3 dense vectors + BM25 via jieba, fused with RRF), document & webpage ingestion, and optional RAG answering via local Ollama. Single process, embedded ChromaDB, REST + native MCP server; fully functional offline without any LLM. Apache-2.0.
Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.
Category & Scope
Tools & Capabilities Breakdown
Rag Kb Tools (0)
No explicit tool names declared in metadata yet. Check project README on main listing page.
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
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).
Rag Kb is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Memora belongs to Knowledge & Memory using local stdio subprocess. Select Rag Kb when you need capabilities focused on knowledge & memory and Memora when you require tools for knowledge & memory.