Claude Concilium
Multi-agent consultation for Claude Code: MCP servers wrapping Codex, Gemini and Qwen CLIs for parallel code review and problem-solving with fallback chains.
Install
The installation steps are in the documentation below. Documentation
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
Claude Concilium
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 | OAuth 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 | OAuth / API key | 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 |
AUTH_NOT_CONFIGURED | Qwen auth type not set | Set QWEN_AUTH_TYPE env var |
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 |
Docker
Run any server in a container:
# Build
docker build -t claude-concilium .
# Run a specific server (mcp-openai | mcp-gemini | mcp-qwen)
docker run -i --rm -e SERVER=mcp-openai claude-concilium
docker run -i --rm -e SERVER=mcp-gemini claude-concilium
Note: The servers wrap CLI tools (codex, gemini, qwen) that require local authentication. Mount your auth credentials when running:
# OpenAI (Codex)
docker run -i --rm -e SERVER=mcp-openai \
-v ~/.codex:/root/.codex:ro \
claude-concilium
# Gemini
docker run -i --rm -e SERVER=mcp-gemini \
-v ~/.config/gemini:/root/.config/gemini:ro \
claude-concilium
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
Changelog
v2.0.0 (2026-03-02)
mcp-qwen:
- Prompt delivery via stdin (
-p -) instead of command argument — safe for any content, no length limits - OAuth auth-type support via
QWEN_AUTH_TYPEenv var (e.g.,qwen-oauth) - New error detection:
AUTH_NOT_CONFIGURED(catches "no auth type is selected") - Graceful shutdown handler (SIGTERM)
mcp-openai:
- Default timeout increased from 90s to 180s (codex exec can be slow on complex prompts)
All servers:
- Version bumped to 2.0.0
- Updated documentation and setup guides
v0.1.0 (2025-12-15)
- Initial release with 3 MCP servers (OpenAI, Gemini, Qwen)
- Concilium skill with fallback chains
- Smoke test suite
- Docker support
License
MIT
Frequently asked questions
What is Claude Concilium?
Multi-agent consultation for Claude Code: MCP servers wrapping Codex, Gemini and Qwen CLIs for parallel code review and problem-solving with fallback chains.
How do I install Claude Concilium?
Follow the installation steps in its documentation, shown on this page and in its repository.
Is Claude Concilium open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains Claude Concilium?
It is published by spyrae. AI.tn lists it but does not maintain or endorse it.
From the community awesome-mcp-servers lists and the project's GitHub repository. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.