What is the key difference between Federated AI Commons and Huntress?

Federated AI Commons belongs to the Security category with local stdio execution, while Huntress belongs to the Security category with local stdio execution.

How do I install Federated AI Commons or Huntress 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 Federated AI Commons and Huntress free or paid?

Federated AI Commons operates under a Free / Open Source model (No auth required). Huntress operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Federated AI Commons lists 0 tools with 2 views and 0 GitHub stars. Huntress lists 0 tools with 1 views and 1 GitHub stars.

Can I use both Federated AI Commons and Huntress 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

Federated AI Commons vs Huntress

In-depth architectural comparison of the Federated AI Commons and Huntress 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

Federated AI Commons

Security · Local stdio

Quality: 41/100 (Fair) | Auth: No auth required

Huntress

Security · Local stdio

Quality: 45/100 (Fair) | Auth: No auth required

Verdict Summary: Choose Federated AI Commons if you need specialized Security tools running via a local process. Choose Huntress if your workspace requires Security integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Federated AI Commons when:

You need dedicated capabilities in the Security domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).

Explore Federated AI Commons Details

Choose Huntress when:

You need dedicated capabilities in the Security domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).

Explore Huntress Details

Feature & Specification Comparison

Specification	Federated AI Commons Security	Huntress Security
Summary	MCP server for a federated AI-commons governance simulation with a verified compliance oracle.	MCP server for Huntress — accounts, organizations, agents, incidents, and reports.
Category & Scope	Security	Security
Quality signal

Tools & Capabilities Breakdown

Federated AI Commons Tools (0)

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

Huntress 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).

Federated AI Commons Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "federated-ai-commons": {
      "command": "uvx",
      "args": [
        "mesa"
      ]
    }
  }
}

Huntress Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "huntress-2": {
      "command": "npx",
      "args": [
        "-y",
        "github:WYRE-AI/huntress-mcp"
      ]
    }
  }
}

Frequently Asked Questions

Federated AI Commons is categorized under Security and uses a local stdio subprocess. In contrast, Huntress belongs to Security using local stdio subprocess. Select Federated AI Commons when you need capabilities focused on security and Huntress when you require tools for security.

More alternatives to Federated AI Commons More alternatives to Huntress Security category hub