What is the key difference between Agently Brain and Rag Knowledge Mcp?

Agently Brain belongs to the Knowledge & Memory category with cloud HTTP/SSE execution, while Rag Knowledge Mcp belongs to the Knowledge & Memory category with local stdio execution.

How do I install Agently Brain or Rag Knowledge Mcp 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 Agently Brain and Rag Knowledge Mcp free or paid?

Agently Brain operates under a Free / Open Source model (No auth required). Rag Knowledge Mcp operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Agently Brain lists 0 tools with 0 views and 0 GitHub stars. Rag Knowledge Mcp lists 0 tools with 0 views and 0 GitHub stars.

Can I use both Agently Brain and Rag Knowledge Mcp 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 Agently Brain or Rag Knowledge Mcp 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 Agently Brain and Rag Knowledge Mcp free to use, or do they require API keys?

Agently Brain is listed under a Free / Open Source model with No auth required . Rag Knowledge Mcp 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 Agently Brain and Rag Knowledge Mcp at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both agently-brain and rag-knowledge-mcp 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, Agently Brain has a Quality Score of 42 /100 ( Fair ) with 0 views, 0 installs, and 0 GitHub stars. Rag Knowledge Mcp holds a Quality Score of 37 /100 ( Fair ) with 0 views, 0 installs, and 0 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Agently Brain vs Rag Knowledge Mcp

In-depth architectural comparison of the Agently Brain and Rag Knowledge Mcp 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

Agently Brain

Knowledge & Memory · Remote HTTP/SSE

Quality: 42/100 (Fair) | Auth: No auth required

Rag Knowledge Mcp

Knowledge & Memory · Local stdio

Quality: 37/100 (Fair) | Auth: No auth required

Verdict Summary: Choose Agently Brain if you need specialized Knowledge & Memory tools running via a hosted cloud SSE transport. Choose Rag Knowledge Mcp 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 Agently Brain 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 Agently Brain Details

Choose Rag Knowledge Mcp 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 Rag Knowledge Mcp Details

Feature & Specification Comparison

Specification	A Agently Brain Knowledge & Memory	R Rag Knowledge Mcp Knowledge & Memory
Summary	Company brain for AI agents — temporal knowledge graph search, exploration, and durable memory.	MCP server for rag knowledge. Features semantic search, knowledge graph query, index documen...
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal

Tools & Capabilities Breakdown

Agently Brain Tools (0)

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

Rag Knowledge Mcp 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).

Agently Brain Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agently-brain": {
      "url": "https://agently.dev/docs/mcp-server"
    }
  }
}

Rag Knowledge Mcp Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "rag-knowledge-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli@latest"
      ]
    }
  }
}

Frequently Asked Questions

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

More alternatives to Agently Brain More alternatives to Rag Knowledge Mcp Knowledge & Memory category hub