What is the key difference between Agentward and Federated Ai Commons?

Agentward belongs to the Security category with local stdio execution, while Federated Ai Commons belongs to the Security category with local stdio execution.

How do I install Agentward or Federated Ai Commons 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 Agentward and Federated Ai Commons free or paid?

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

Which MCP server has more tools and community activity?

Agentward lists 14 tools with 2 views and 19 GitHub stars. Federated Ai Commons lists 0 tools with 1 views and 0 GitHub stars.

Can I use both Agentward and Federated Ai Commons 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 Agentward or Federated Ai Commons 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 Agentward and Federated Ai Commons free to use, or do they require API keys?

Agentward is listed under a Free / Open Source model with No auth required . Federated Ai Commons 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 Agentward and Federated Ai Commons at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both agentward-ai-agentward and federated-ai-commons 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, Agentward has a Quality Score of 67 /100 ( Great ) with 2 views, 0 installs, and 19 GitHub stars. Federated Ai Commons holds a Quality Score of 27 /100 ( Emerging ) with 1 views, 0 installs, and 0 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Agentward vs Federated Ai Commons

In-depth architectural comparison of the Agentward and Federated Ai Commons 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

Agentward

Security · Local stdio

Quality: 67/100 (Great) | Auth: No auth required

Federated Ai Commons

Security · Local stdio

Quality: 27/100 (Emerging) | Auth: No auth required

Verdict Summary: Choose Agentward if you need specialized Security tools running via a local process. Choose Federated Ai Commons 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 Agentward 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).
Primary tools included: read_file, read_text_file, read_media_file.

Explore Agentward Details

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

Feature & Specification Comparison

Specification	Agentward agentward-ai Security	F Federated Ai Commons Security
Summary	Permission control plane for AI agents. MCP proxy that enforces least-privilege YAML policies on every tool call, classifies sensitive data (PII/PHI), detects dangerous skill chains, and generates compliance audit trails. Supports stdio and HTTP proxy modes.	MCP server for a federated AI-commons governance simulation with a verified compliance oracle.
Category & Scope	Security

Tools & Capabilities Breakdown

Agentward Tools (14)

read_file

Read the complete contents of a file as text. DEPRECATED: Use read_text_file instead.

read_text_file

Read the complete contents of a file from the file system as text. Handles various text encodings and provides detailed error messages if the file cannot be read. Use this tool when you need to examine the contents of a single file. Use the 'head' parameter to read only the first N lines of a file, or the 'tail' parameter to read only the last N lines of a file. Operates on the file as text regardless of extension. Only works within allowed directories.

read_media_file

Read a file and return it as a base64-encoded content block with its MIME type. Image and audio files are returned as image/audio content; any other file type is returned as an embedded resource. Only works within allowed directories.

read_multiple_files

Read the contents of multiple files simultaneously. This is more efficient than reading files one by one when you need to analyze or compare multiple files. Each file's content is returned with its path as a reference. Failed reads for individual files won't stop the entire operation. Only works within allowed directories.

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).

Agentward Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "agentward-ai-agentward": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem"
      ]
    }
  }
}

Federated Ai Commons Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "federated-ai-commons": {
      "command": "npx",
      "args": [
        "-y",
        "federated-ai-commons"
      ]
    }
  }
}

Frequently Asked Questions

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

More alternatives to Agentward More alternatives to Federated Ai Commons Security category hub