CCG MCP Tool (Claude Code/Codex/Gemini)

This is a powerful Model Context Protocol (MCP) server that integrates multiple AI coding agents—Anthropic Claude Code, OpenAI Codex, and Google Gemini—directly into your workflow. It enables seamless cross-provider analysis, leveraging Gemini's massive token window, Codex's specialized coding capabilities, and Claude's advanced reasoning.

Ask any supported AI for its perspective.
Brainstorm ideas with multi-provider frameworks.
New: Apply research-grounded mitigation skills to avoid common AI coding mistakes.

Goal: Use the best AI for the job. Analyze massive codebases with Gemini, get precision edits with Codex, or use Claude's reasoning—all from a single MCP interface.

Prerequisites

Ensure you have the following CLI tools installed and configured:

Node.js (v16.0.0 or higher)
Google Gemini CLI
Codex CLI (optional)
Claude Code (optional)

Installation

claude mcp add ccg-tool -- npx -y ccg-mcp-tool

Configuration

For NPX Usage (Recommended)

Add this configuration to your Claude Desktop config file:

{
  "mcpServers": {
    "ccg-tool": {
      "command": "npx",
      "args": [
        "-y", 
        "ccg-mcp-tool",
        "--provider",
        "claude",
        "--model",
        "sonnet"
      ]
    }
  }
}

Note: The --provider and --model startup arguments set the global default for all tool calls in your session. Tools still support overriding these per-request.

Example Workflow

Multi-Provider: ask ai --provider codex to refactor @src/auth.ts
Mistake Mitigation: mitigate mistakes --skill requirements-grounding for @new-feature.md
Gemini Specific: ask ai --provider gemini to analyze @. and explain the architecture

Tools (for the AI)

`ask-ai`

Universal tool for AI analysis across providers.

prompt (required): Your request. Use @ for files.
provider (optional): gemini, codex, or claude. Defaults to server config.
model (optional): Specific model for the provider (e.g., gemini-2.5-flash, sonnet, opus). Claude uses aliases (sonnet, opus, haiku) or full names.
sandbox (optional): Gemini-only. Run in an isolated environment.
changeMode (optional): Gemini-only. Returns structured edits.

`mitigate-mistakes`

Apply research-grounded gates to prevent common AI agent failure modes.

skill (required): The mitigation gate to apply (e.g., requirements-grounding, secure-coding-and-validation-gate).
prompt (required): The task or code to analyze.
provider (optional): Which AI to use for the assessment.

Available Skills:

requirements-grounding: Prevent requirement-conflicting hallucinations.
context-scope-discipline: Maintain focus on the requested change set.
dependency-verification: Verify imports and versions.
design-doc-and-architecture-gate: Ensure structural integrity.
test-and-error-path-gate: Validate edge cases and failure modes.
secure-coding-and-validation-gate: Identify security risks (unbiased).
code-quality-enforcer: Check for maintainability and patterns.
deterministic-validation-gate: Use evidence-based checks.
code-review-and-change-gate: Final gate before application.

`brainstorm`

Generate ideas using structured methodologies like SCAMPER or Design Thinking.

methodology: divergent, convergent, scamper, lateral, etc.
domain: Specialized context (e.g., software, security).

License

MIT License.

Disclaimer: This is an unofficial tool and is not affiliated with Google, OpenAI, or Anthropic.

ccg-mcp-tool