What is the key difference between Memora and Rag Kb?

Memora belongs to the Knowledge & Memory category with local stdio execution, while Rag Kb belongs to the Knowledge & Memory category with local stdio execution.

How do I install Memora or Rag Kb in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Memora and Rag Kb free or paid?

Memora operates under a BYOK (Pay Provider Direct) model (API Key required). Rag Kb operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Memora lists 6 tools with 2 views and 719 GitHub stars. Rag Kb lists 0 tools with 0 views and 2 GitHub stars.

Can I use both Memora and Rag Kb together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

Side-by-Side Model Context Protocol Comparison

Memora vs Rag Kb

In-depth architectural comparison of the Memora and Rag Kb 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: 56/100 (Good) | Auth: API Key required

Rag Kb

Knowledge & Memory · Local stdio

Quality: 45/100 (Fair) | Auth: No auth required

Verdict Summary: Choose Memora if you need specialized Knowledge & Memory tools running via a local process. Choose Rag Kb 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.

Explore Memora Details

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).

Feature & Specification Comparison

Specification	Memora agentic-mcp-tools Knowledge & Memory	Rag Kb fish827-08 Knowledge & Memory
Summary	Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.	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.
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

Rag Kb Tools (0)

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 Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agentic-mcp-tools-memora": {
      "command": "npx",
      "args": [
        "-y",
        "wrangler"
      ],
      "env": {
        "MEMORA_DB_PATH": "YOUR_MEMORA_DB_PATH_HERE",
        "MEMORA_STORAGE_URI": "YOUR_MEMORA_STORAGE_URI_HERE",
        "CLOUDFLARE_API_TOKEN": "YOUR_CLOUDFLARE_API_TOKEN_HERE",
        "AWS_PROFILE": "YOUR_AWS_PROFILE_HERE",
        "AWS_ENDPOINT_URL": "YOUR_AWS_ENDPOINT_URL_HERE",
        "MEMORA_CLOUD_ENCRYPT": "YOUR_MEMORA_CLOUD_ENCRYPT_HERE",
        "MEMORA_ALLOW_ANY_TAG": "YOUR_MEMORA_ALLOW_ANY_TAG_HERE",
        "MEMORA_GRAPH_PORT": "YOUR_MEMORA_GRAPH_PORT_HERE"
      }
    }
  }
}

Rag Kb Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "fish827-08-rag-kb": {
      "command": "npx",
      "args": [
        "-y",
        "fish827-08-rag-kb"
      ]
    }
  }
}

Frequently Asked Questions

Memora is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Rag Kb belongs to Knowledge & Memory using local stdio subprocess. Select Memora when you need capabilities focused on knowledge & memory and Rag Kb when you require tools for knowledge & memory.

More alternatives to Memora More alternatives to Rag Kb Knowledge & Memory category hub