What is the key difference between Epiphany and Shelfmark?

Epiphany belongs to the Knowledge & Memory category with cloud HTTP/SSE execution, while Shelfmark belongs to the Knowledge & Memory category with local stdio execution.

How do I install Epiphany or Shelfmark 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 Epiphany and Shelfmark free or paid?

Epiphany operates under a Free / Open Source model (No auth required). Shelfmark operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Epiphany lists 0 tools with 0 views and 1 GitHub stars. Shelfmark lists 0 tools with 0 views and 0 GitHub stars.

Can I use both Epiphany and Shelfmark 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.

How do I install Epiphany or Shelfmark in Claude Desktop, Cursor, or Windsurf?

Both servers follow the standard Model Context Protocol configuration format. Simply copy the JSON block from the configuration section above and paste it into your AI client's mcpServers configuration object (for instance in claude_desktop_config.json or ~/.cursor/mcp.json ), then completely restart or refresh the application.

Are Epiphany and Shelfmark free to use, or do they require API keys?

Epiphany is listed under a Free / Open Source model with No auth required . Shelfmark operates under a Free / Open Source model with No auth required . If environment variables are required (such as API keys), be sure to define them under the env key in your MCP client's configuration file.

Can I run both Epiphany and Shelfmark at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both epiphany and shelfmark as distinct keys inside the single mcpServers object in your configuration file. Your AI assistant will automatically select and call the appropriate tool from either server during chat sessions.

Which MCP server has higher directory engagement and quality ratings?

On AllMCPs, Epiphany has a Quality Score of 43 /100 ( Fair ) with 0 views, 0 installs, and 1 GitHub stars. Shelfmark holds a Quality Score of 33 /100 ( Emerging ) with 0 views, 0 installs, and 0 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Epiphany vs Shelfmark

In-depth architectural comparison of the Epiphany and Shelfmark 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

Epiphany

Knowledge & Memory · Remote HTTP/SSE

Quality: 43/100 (Fair) | Auth: No auth required

Shelfmark

Knowledge & Memory · Local stdio

Quality: 33/100 (Emerging) | Auth: No auth required

Verdict Summary: Choose Epiphany if you need specialized Knowledge & Memory tools running via a hosted cloud SSE transport. Choose Shelfmark 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 Epiphany when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer remote streaming HTTP/SSE transport architecture.
Your security boundary fits: No auth required (Free / Open Source).

Explore Epiphany Details

Choose Shelfmark 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).

Explore Shelfmark Details

Feature & Specification Comparison

Specification	E Epiphany Knowledge & Memory	S Shelfmark Knowledge & Memory
Summary	One private, local memory your AI tools share. Cross-model, on-device, never lose a session.	Local, privacy-first document catalogue for AI agents: metadata-only discovery, no cloud, no RAG.
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal

Tools & Capabilities Breakdown

Epiphany Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

Shelfmark Tools (0)

No explicit tool names declared in metadata yet. Check project README on main listing page.

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).

Epiphany Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "epiphany": {
      "url": "https://modelcontextprotocol.io"
    }
  }
}

Shelfmark Configuration

mcpServers (Claude Desktop / Cursor)

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

Frequently Asked Questions

Epiphany is categorized under Knowledge & Memory and uses a remote streaming HTTP/SSE transport. In contrast, Shelfmark belongs to Knowledge & Memory using local stdio subprocess. Select Epiphany when you need capabilities focused on knowledge & memory and Shelfmark when you require tools for knowledge & memory.

More alternatives to Epiphany More alternatives to Shelfmark Knowledge & Memory category hub