What is the key difference between Agent Recall and Darwin RAG?

Agent Recall belongs to the Knowledge & Memory category with local stdio execution, while Darwin RAG belongs to the Knowledge & Memory category with local stdio execution.

How do I install Agent Recall or Darwin RAG 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 Agent Recall and Darwin RAG free or paid?

Agent Recall operates under a Free / Open Source model (No auth required). Darwin RAG operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Agent Recall lists 0 tools with 1 views and 365 GitHub stars. Darwin RAG lists 0 tools with 0 views and 0 GitHub stars.

Can I use both Agent Recall and Darwin RAG 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 Agent Recall or Darwin RAG 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 Agent Recall and Darwin RAG free to use, or do they require API keys?

Agent Recall is listed under a Free / Open Source model with No auth required . Darwin RAG 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 Agent Recall and Darwin RAG at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both agent-recall and darwin-rag 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, Agent Recall has a Quality Score of 47 /100 ( Fair ) with 1 views, 0 installs, and 365 GitHub stars. Darwin RAG holds a Quality Score of 25 /100 ( Emerging ) with 0 views, 0 installs, and 0 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Agent Recall vs Darwin RAG

In-depth architectural comparison of the Agent Recall and Darwin RAG 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

Agent Recall

Knowledge & Memory · Local stdio

Quality: 47/100 (Fair) | Auth: No auth required

Darwin RAG

Knowledge & Memory · Local stdio

Quality: 25/100 (Emerging) | Auth: No auth required

Verdict Summary: Choose Agent Recall if you need specialized Knowledge & Memory tools running via a local process. Choose Darwin RAG 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 Agent Recall 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 Agent Recall Details

Choose Darwin RAG 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 Darwin RAG Details

Feature & Specification Comparison

Specification	A Agent Recall Knowledge & Memory	D Darwin RAG Knowledge & Memory
Summary	Correction-first agent memory. Precision KPI tracks if agents heed warnings. 5 layers, local-only.	Local-first RAG engine with MCP server for AI agent integration.
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal

Tools & Capabilities Breakdown

Agent Recall Tools (0)

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

Darwin RAG 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).

Agent Recall Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agent-recall": {
      "command": "npx",
      "args": [
        "-y",
        "agent-recall-mcp"
      ]
    }
  }
}

Darwin RAG Configuration

mcpServers (Claude Desktop / Cursor)

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

Frequently Asked Questions

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

More alternatives to Agent Recall More alternatives to Darwin RAG Knowledge & Memory category hub