What is the key difference between Memora and MemoryMesh?

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

How do I install Memora or MemoryMesh 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 MemoryMesh free or paid?

Memora operates under a BYOK (Pay Provider Direct) model (API Key required). MemoryMesh 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. MemoryMesh lists 6 tools with 1 views and 353 GitHub stars.

Can I use both Memora and MemoryMesh 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 MemoryMesh

In-depth architectural comparison of the Memora and MemoryMesh 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

MemoryMesh

Knowledge & Memory · Local stdio

Quality: 36/100 (Fair) | Auth: No auth required

Verdict Summary: Choose Memora if you need specialized Knowledge & Memory tools running via a local process. Choose MemoryMesh 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 MemoryMesh 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	MemoryMesh CheMiguel23 Knowledge & Memory
Summary	Persistent memory with knowledge graph visualization, semantic/hybrid search, cloud sync (S3/R2), and cross-session context management.	Enhanced graph-based memory with a focus on AI role-play and story generation
Category & Scope	Knowledge & Memory

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

MemoryMesh 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 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"
      }
    }
  }
}

MemoryMesh Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "chemiguel23-memorymesh": {
      "command": "npx",
      "args": [
        "-y",
        "chemiguel23-memorymesh"
      ]
    }
  }
}

Frequently Asked Questions

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

More alternatives to Memora More alternatives to MemoryMesh Knowledge & Memory category hub