What is the key difference between Kagan and Agent MCP?

Kagan belongs to the Coding Agents category with cloud HTTP/SSE execution, while Agent MCP belongs to the Coding Agents category with local stdio execution.

How do I install Kagan or Agent 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 Kagan and Agent MCP free or paid?

Kagan operates under a Free / Open Source model (No auth required). Agent MCP operates under a BYOK (Pay Provider Direct) model (API Key required).

Which MCP server has more tools and community activity?

Kagan lists 5 tools with 3 views and 7 GitHub stars. Agent MCP lists 12 tools with 3 views and 1,272 GitHub stars.

Can I use both Kagan and Agent 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 Kagan or Agent 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 Kagan and Agent MCP free to use, or do they require API keys?

Kagan is listed under a Free / Open Source model with No auth required . Agent MCP operates under a BYOK (Pay Provider Direct) model with API Key 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 Kagan and Agent MCP at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both kagan-sh-kagan and rinadelph-agent-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, Kagan has a Quality Score of 53 /100 ( Good ) with 3 views, 0 installs, and 7 GitHub stars. Agent MCP holds a Quality Score of 52 /100 ( Good ) with 3 views, 0 installs, and 1,272 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Kagan vs Agent MCP

In-depth architectural comparison of the Kagan and Agent 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

Kagan

Coding Agents · Remote HTTP/SSE

Quality: 53/100 (Good) | Auth: No auth required

Agent MCP

Coding Agents · Local stdio

Quality: 52/100 (Good) | Auth: API Key required

Verdict Summary: Choose Kagan if you need specialized Coding Agents tools running via a hosted cloud SSE transport. Choose Agent MCP if your workspace requires Coding Agents integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Kagan when:

You need dedicated capabilities in the Coding Agents domain.
You prefer remote streaming HTTP/SSE transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: Supervised kanban board for AI agent tasks, Isolated git worktrees per task on dedicated branches, Task lifecycle with intake, review, and merge gates.

Explore Kagan Details

Choose Agent MCP when:

You need dedicated capabilities in the Coding Agents domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (BYOK (Pay Provider Direct)).
You have access to required keys: OPENAI_API_KEY.
Primary tools included: create_agent, list_agents, terminate_agent.

Explore Agent MCP Details

Feature & Specification Comparison

Specification	Kagan kagan-sh Coding Agents	Agent MCP rinadelph Coding Agents
Summary	AI-powered Kanban TUI and MCP server for autonomous development workflows. Orchestrates 14 coding agents across task tracking, isolated git worktrees, review, and merge.	A framework for creating multi-agent systems using MCP for coordinated AI collaboration, featuring task management, shared context, and RAG capabilities.
Category & Scope	Coding Agents

Tools & Capabilities Breakdown

Kagan Tools (5)

Supervised kanban board for AI agent tasks

Isolated git worktrees per task on dedicated branches

Task lifecycle with intake, review, and merge gates

Integration as an OpenCode plugin

Agent findings ranked and triaged before merge

Agent MCP Tools (12)

create_agent

list_agents

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).

Kagan Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "kagan-sh-kagan": {
      "url": "https://raw.githubusercontent.com/kagan-sh/kagan/main/docs/public/favicon.svg"
    }
  }
}

Agent MCP Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "rinadelph-agent-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "rinadelph-agent-mcp"
      ],
      "env": {
        "OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE"
      }
    }
  }
}

Frequently Asked Questions

Kagan is categorized under Coding Agents and uses a remote streaming HTTP/SSE transport. In contrast, Agent MCP belongs to Coding Agents using local stdio subprocess. Select Kagan when you need capabilities focused on coding agents and Agent MCP when you require tools for coding agents.

More alternatives to Kagan More alternatives to Agent MCP Coding Agents category hub