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

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

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

Federated Ai Commons operates under a Free / Open Source model (No auth required). Agentward 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 0 views and 0 GitHub stars. Agentward lists 14 tools with 2 views and 19 GitHub stars.

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

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

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

Side-by-Side Model Context Protocol Comparison

Federated Ai Commons vs Agentward

In-depth architectural comparison of the Federated Ai Commons and Agentward 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: 27/100 (Emerging) | Auth: No auth required

Agentward

Security · Local stdio

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

Verdict Summary: Choose Federated Ai Commons if you need specialized Security tools running via a local process. Choose Agentward 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 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

Feature & Specification Comparison

Specification	F Federated Ai Commons Security	Agentward agentward-ai Security
Summary	MCP server for a federated AI-commons governance simulation with a verified compliance oracle.	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.
Category & Scope	Security

Tools & Capabilities Breakdown

Federated Ai Commons Tools (0)

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

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

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

Agentward Configuration

mcpServers (Claude Desktop / Cursor)

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

Frequently Asked Questions

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

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