shiharuharu/cli-agent-mcp

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Unified MCP (Model Context Protocol) server for CLI AI agents. Provides a single interface to invoke Codex, Gemini, Claude, OpenCode CLI tools, and Nano Banana Pro image generation.

Обзор

Unified MCP (Model Context Protocol) server for CLI AI agents. Provides a single interface to invoke Codex, Gemini, Claude, OpenCode CLI tools, and Nano Banana Pro image generation. This is more than a CLI wrapper — it's an for multi-model collaboration. Let Claude orchestrate. Describe what you want, and it will decompose your vague idea into concrete tasks for the right agent. The act of delegation forces clarity. Each model brings a unique lens: - : The critic. Its analytical eye catches what you missed, challenges assumptions, finds edge cases. - : The creative. Divergent thinking, unexpected connections, the spark you didn't know you needed. - : The scribe. Faithful execution, clear documentation, turning ideas into working code. - : The artist. High-fidelity image generation for UI mockups, product visuals, and creative assets. Use handoff_file to capture agent outputs, then let Claude synthesize insights across multiple analyses.

README

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cli-agent-mcp

中文文档

Unified MCP (Model Context Protocol) server for CLI AI agents. Provides a single interface to invoke Codex, Gemini, Claude, OpenCode CLI tools, and Nano Banana Pro image generation.

Why cli-agent-mcp?

This is more than a CLI wrapper — it’s an orchestration pattern for multi-model collaboration.

Can’t articulate your requirements clearly? Let Claude orchestrate. Describe what you want, and it will decompose your vague idea into concrete tasks for the right agent. The act of delegation forces clarity.

Planning a grand product vision? Each model brings a unique lens:

Codex: The critic. Its analytical eye catches what you missed, challenges assumptions, finds edge cases.
Gemini: The creative. Divergent thinking, unexpected connections, the spark you didn’t know you needed.
Claude: The scribe. Faithful execution, clear documentation, turning ideas into working code.
Banana: The artist. High-fidelity image generation for UI mockups, product visuals, and creative assets.

Want persistent results? Use handoff_file to capture agent outputs, then let Claude synthesize insights across multiple analyses.

We don’t just wrap CLIs — we provide a thinking framework for human-AI collaboration.

Features

Unified Interface: Single MCP server exposing multiple CLI agents
GUI Dashboard: Real-time task monitoring with pywebview
Request Isolation: Per-request execution context for safe concurrent usage
Signal Handling: Graceful cancellation via SIGINT without killing the server
Debug Logging: Comprehensive subprocess output capture for debugging

Screenshot

Installation

# Install from PyPI (when published)
uvx cli-agent-mcp

# Install from GitHub
uvx --from git+https://github.com/shiharuharu/cli-agent-mcp.git cli-agent-mcp

# Install from source (editable mode for development)
uvx --from /path/to/cli-agent-mcp cli-agent-mcp

# Or use pip
pip install -e .

Configuration

Configure via environment variables:

Variable	Description	Default
`CAM_ENABLE`	Comma-separated list of enabled tools (empty = all)	`""` (all)
`CAM_DISABLE`	Comma-separated list of disabled tools (subtracted from enable)	`""`
`CAM_GUI`	Enable GUI dashboard	`true`
`CAM_GUI_DETAIL`	GUI detail mode	`false`
`CAM_GUI_KEEP`	Keep GUI on exit	`false`
`CAM_GUI_HOST`	GUI bind host	`127.0.0.1`
`CAM_GUI_PORT`	GUI bind port (set a fixed port to keep URL stable across restarts)	`0` (random)
`CAM_DEBUG`	Include debug info in MCP responses	`false`
`CAM_LOG_DEBUG`	Write debug logs to temp file	`false`
`CAM_SIGINT_MODE`	SIGINT handling (`cancel`/`exit`/`cancel_then_exit`)	`cancel`
`CAM_SIGINT_DOUBLE_TAP_WINDOW`	Double-tap exit window (seconds)	`1.0`

Tools

codex

Открыть полный README на GitHub

Установка

uvx cli-agent-mcp

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Конфигурация

{
  "mcpServers": {
    "cli-agent-mcp": {
      "command": "uvx",
      "args": ["cli-agent-mcp"]
    }
  }
}