# Claude Concilium
[](https://opensource.org/licenses/MIT)
[](https://nodejs.org/)
[](https://modelcontextprotocol.io/)
[](#mcp-servers)
[](#quickstart)
<a href="https://glama.ai/mcp/servers/@spyrae/claude-concilium">
<img width="380" height="200" src="https://glama.ai/mcp/servers/@spyrae/claude-concilium/badge" alt="Claude Concilium MCP server" />
</a>
**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](https://modelcontextprotocol.io/). 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
```bash
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](docs/setup-openai.md) |
| **Gemini** | Google OAuth | 1000 req/day | [Setup guide](docs/setup-gemini.md) |
| **Qwen** | `qwen login` or API key | Varies | [Setup guide](docs/setup-qwen.md) |
| **DeepSeek** | API key | Pay-per-use (cheap) | [Setup guide](docs/setup-deepseek.md) |
### 3. Add to Claude Code
Copy `config/mcp.json.example` and update paths:
```bash
# 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`:
```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:
```bash
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](servers/mcp-openai/) | `codex` | OAuth (ChatGPT Plus) | `openai_chat`, `openai_review` |
| [mcp-gemini](servers/mcp-gemini/) | `gemini` | Google OAuth | `gemini_chat`, `gemini_analyze` |
| [mcp-qwen](servers/mcp-qwen/) | `qwen` | API key / CLI login | `qwen_chat` |
**DeepSeek** uses the existing [`deepseek-mcp-server`](https://www.npmjs.com/package/deepseek-mcp-server) npm package — no custom server needed.
## How It Works
### Consultation Flow
1. **Formulate** — describe the problem concisely (under 500 chars)
2. **Send in parallel** — OpenAI + Gemini get the same prompt
3. **Handle errors** — if a provider fails, fallback chain kicks in (Qwen → DeepSeek)
4. **Synthesize** — compare responses, find consensus
5. **Iterate** (optional) — resolve disagreements with follow-up questions
6. **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 |
## Docker
Run any server in a container:
```bash
# 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:
```bash
# 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](docs/customization.md) for:
- Adding your own LLM provider
- Modifying the fallback chain
- MCP server template
- Custom prompt strategies
## Documentation
- [Architecture](docs/architecture.md) — flow diagrams, error handling, design decisions
- [OpenAI Setup](docs/setup-openai.md) — Codex CLI, ChatGPT Plus, minimal config
- [Gemini Setup](docs/setup-gemini.md) — gemini-cli, Google OAuth
- [Qwen Setup](docs/setup-qwen.md) — Qwen CLI, DashScope
- [DeepSeek Setup](docs/setup-deepseek.md) — API key, npm package
- [Customization](docs/customization.md) — add your own LLM, modify chains
## License
MIT
