claude-concilium

# DeepSeek Concilium

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Node.js 20+](https://img.shields.io/badge/node-20%2B-brightgreen.svg)](https://nodejs.org/)
[![MCP Protocol](https://img.shields.io/badge/MCP-2024--11--05-blue.svg)](https://modelcontextprotocol.io/)
[![Servers](https://img.shields.io/badge/MCP_Servers-3-orange.svg)](#mcp-servers)
[![Version](https://img.shields.io/badge/version-2.0.0-blue.svg)](#changelog)
[![Smoke Tests](https://img.shields.io/badge/tests-passing-brightgreen.svg)](#quickstart)

<a href="https://glama.ai/mcp/servers/@spyrae/deepseek-concilium">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/@spyrae/deepseek-concilium/badge" alt="DeepSeek 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
              ├── DeepSeek (deepseek-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 fo