ApeRAG vs Cognee

In-depth architectural comparison of the ApeRAG and Cognee 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.

Which MCP Server Should You Choose?

Choose ApeRAG when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer remote streaming HTTP/SSE transport architecture.
• Your security boundary fits: API Key required (Free / Open Source).
• You have access to required keys: APERAG_API_KEY, DOCRAY_HOST.
• Primary tools included: Five index types: vector, full-text, graph, summary, vision, Built-in AI agents with MCP tool support, Advanced entity normalization for cleaner knowledge graphs.

Explore ApeRAG Details

Choose Cognee 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: LLM_API_KEY.
• Primary tools included: Supports ingestion from 30+ data sources, Combines vector embeddings with graph-based reasoning, Self-hosted knowledge graph with ontology generation.

Feature & Specification Comparison

Specification	ApeRAG apecloud Knowledge & Memory	Cognee topoteretes Knowledge & Memory
Summary	Production-ready RAG platform combining Graph RAG, vector search, and full-text search. Best choice for building your own Knowledge Graph and for Context Engineering	Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources
Category & Scope	Knowledge & Memory

Tools & Capabilities Breakdown

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).

{
  "mcpServers": {
    "apecloud-aperag": {
      "url": "https://archestra.ai/mcp-catalog/api/badge/quality/apecloud/ApeRAG)](https://archestra.ai/mcp-catalog/apecloud__aperag"
    }
  }
}

{
  "mcpServers": {
    "topoteretes-cognee": {
      "command": "npx",
      "args": [
        "-y",
        "topoteretes-cognee"
      ],
      "env": {
        "LLM_API_KEY": "YOUR_LLM_API_KEY_HERE"
      }
    }
  }
}

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