Which integrations are available for this server?

Enables interaction with Google's Gemini models using Google OAuth to provide chat and analysis tools as part of a parallel consultation workflow. Integrates OpenAI models via the Codex CLI to perform code reviews and chat consultations using OAuth-authenticated sessions.

Claude Concilium

License: MIT Node.js 18+ MCP Protocol Servers Smoke Tests

Multi-agent AI consultation framework for Claude Code via MCP.

Get a second (and third) opinion from other LLMs when Claude Code alone isn't enough.

Claude Code ──┬── OpenAI (Codex CLI) ──► Opinion A ├── Gemini (gemini-cli) ─► Opinion B │ └── Synthesis ◄── Consensus or iterate

The Problem

Claude Code is powerful, but one brain can miss bugs, overlook edge cases, or get stuck in a local optimum. Critical decisions benefit from diverse perspectives.

The Solution

Concilium runs parallel consultations with multiple LLMs through standard MCP protocol. Each LLM server wraps a CLI tool — no API keys needed for the primary providers (they use OAuth).

Key features:

Parallel consultation with 2+ AI agents
Production-grade fallback chains with error detection
Each MCP server works standalone or as part of Concilium
Plug & play: clone, npm install, add to .mcp.json

Architecture

┌─────────────────────────────────────────────────────────┐ │ Claude Code │ │ │ │ "Review this code for race conditions" │ │ │ │ ┌──────────────┐ ┌──────────────┐ │ │ │ MCP Call #1 │ │ MCP Call #2 │ (parallel) │ │ └──────┬───────┘ └──────┬───────┘ │ │ │ │ │ └─────────┼──────────────────┼──────────────────────────────┘ │ │ ▼ ▼ ┌──────────────┐ ┌──────────────┐ │ mcp-openai │ │ mcp-gemini │ Primary agents │ (codex exec)│ │ (gemini -p) │ └──────┬───────┘ └──────┬───────┘ │ │ ▼ ▼ ┌──────────────┐ ┌──────────────┐ │ OpenAI │ │ Google │ LLM providers │ (OAuth) │ │ (OAuth) │ └──────────────┘ └──────────────┘ Fallback chain (on quota/error): OpenAI → Qwen → DeepSeek Gemini → Qwen → DeepSeek

Quickstart

1. Clone and install

git clone https://github.com/spyrae/claude-concilium.git cd claude-concilium # Install dependencies for each server cd servers/mcp-openai && npm install && cd ../.. cd servers/mcp-gemini && npm install && cd ../.. cd servers/mcp-qwen && npm install && cd ../.. # Verify all servers work (no CLI tools required) node test/smoke-test.mjs

Expected output:

PASS mcp-openai (Tools: openai_chat, openai_review) PASS mcp-gemini (Tools: gemini_chat, gemini_analyze) PASS mcp-qwen (Tools: qwen_chat) All tests passed.

2. Set up providers

Pick at least 2 providers:

Provider	Auth	Free Tier	Setup
OpenAI	`codex login` (OAuth)	ChatGPT Plus weekly credits	Setup guide
Gemini	Google OAuth	1000 req/day	Setup guide
Qwen	`qwen login` or API key	Varies	Setup guide
DeepSeek	API key	Pay-per-use (cheap)	Setup guide

3. Add to Claude Code

Copy config/mcp.json.example and update paths:

# Edit the example with your actual paths cp config/mcp.json.example .mcp.json # Update "/path/to/claude-concilium" with actual path

Or add servers individually to your existing .mcp.json:

{ "mcpServers": { "mcp-openai": { "type": "stdio", "command": "node", "args": ["/absolute/path/to/servers/mcp-openai/server.js"], "env": { "CODEX_HOME": "~/.codex-minimal" } }, "mcp-gemini": { "type": "stdio", "command": "node", "args": ["/absolute/path/to/servers/mcp-gemini/server.js"] } } }

4. Install the skill (optional)

Copy the Concilium skill to your Claude Code commands:

cp skill/ai-concilium.md ~/.claude/commands/ai-concilium.md

Now use /ai-concilium in Claude Code to trigger a multi-agent consultation.

MCP Servers

Each server can be used independently — you don't need all of them.

Server	CLI Tool	Auth	Tools
mcp-openai	`codex`	OAuth (ChatGPT Plus)	`openai_chat`, `openai_review`
mcp-gemini	`gemini`	Google OAuth	`gemini_chat`, `gemini_analyze`
mcp-qwen	`qwen`	API key / CLI login	`qwen_chat`

DeepSeek uses the existing deepseek-mcp-server npm package — no custom server needed.

How It Works

Consultation Flow

Formulate — describe the problem concisely (under 500 chars)
Send in parallel — OpenAI + Gemini get the same prompt
Handle errors — if a provider fails, fallback chain kicks in (Qwen → DeepSeek)
Synthesize — compare responses, find consensus
Iterate (optional) — resolve disagreements with follow-up questions
Decide — apply the synthesized solution

Error Detection

All servers detect provider-specific errors and return structured responses:

Error Type	Meaning	Action
`QUOTA_EXCEEDED`	Rate/credit limit hit	Use fallback provider
`AUTH_EXPIRED` / `AUTH_REQUIRED`	Token needs refresh	Re-authenticate CLI
`MODEL_NOT_SUPPORTED`	Model unavailable on plan	Use default model
Timeout	Process hung	Auto-killed, use fallback

Fallback Chain

Primary: OpenAI ──────────────► Response (QUOTA_EXCEEDED?) │ Fallback 1: Qwen ──┴────────────► Response (timeout?) │ Fallback 2: DeepSeek ───────────► Response (always available)

When to Use Concilium

Scenario	Recommended Agents
Code review	OpenAI + Gemini (parallel)
Architecture decision	OpenAI + Gemini → iterate if disagree
Stuck bug (3+ attempts)	All available agents
Performance optimization	Gemini (1M context) + OpenAI
Security review	OpenAI + Gemini + manual verification

Customization

See docs/customization.md for:

Adding your own LLM provider
Modifying the fallback chain
MCP server template
Custom prompt strategies

Documentation

Architecture — flow diagrams, error handling, design decisions
OpenAI Setup — Codex CLI, ChatGPT Plus, minimal config
Gemini Setup — gemini-cli, Google OAuth
Qwen Setup — Qwen CLI, DashScope
DeepSeek Setup — API key, npm package
Customization — add your own LLM, modify chains

License

MIT

claude-concilium