
Tetrad
- 1 repo stars
- Updated January 29, 2026
- SamoraDC/Tetrad
Tetrad is a MCP server that runs quadruple consensus code validation using Codex, Gemini, and Qwen.
About
Tetrad is a Model Context Protocol server that runs quadruple consensus code validation by routing the same snippet or diff through Codex, Gemini, and Qwen so you see where models align and where they diverge. developers shipping with Claude Code or Cursor can register @samoradc/tetrad over stdio and treat it as a structured second opinion layer before merge, especially when a single assistant might miss edge cases or security nuances. Version 0.1.12 is distributed on npm; you configure the underlying model credentials according to the project README on GitHub. Tetrad does not replace unit tests, linters, or human review—it compresses multi-LLM scrutiny into one MCP call pattern. Use it when you want ensemble-style validation without manually pasting code into three separate chat tabs, and skip it when you only need fast single-model explanations or your stack cannot call the supported providers.
- Quadruple consensus validation across Codex, Gemini, and Qwen model backends
- Published as npm package @samoradc/tetrad v0.1.12 with stdio MCP transport
- MCP server purpose-built for code validation, not generic chat
- Fits pre-merge and PR-review workflows inside agent-driven development
- Open source on GitHub at SamoraDC/Tetrad
Tetrad by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
claude mcp add tetrad -- npx -y @samoradc/tetradAdd your badge
Show developers this MCP server is listed on Skillselion. Paste this into your README.
| repo stars | ★ 1 |
|---|---|
| Package | @samoradc/tetrad |
| Transport | STDIO |
| Auth | None |
| Last updated | January 29, 2026 |
| Repository | SamoraDC/Tetrad ↗ |
What it does
Run a four-model consensus pass on a code change so Codex, Gemini, and Qwen critiques surface agreement and disagreements before you merge.
Who is it for?
Best when you already use multiple LLM APIs and want an MCP-native ensemble review step on critical patches.
Skip if: Skip if you only want linting and CI, or developers and cannot configure access to the Codex, Gemini, and Qwen backends Tetrad orchestrates.
What you get
After registration, you can invoke consensus validation from your agent and compare multi-model findings before you merge or release.
- Consensus-oriented validation output aggregating multiple model perspectives on submitted code
- Stdio MCP integration for agent-triggered review sessions
- Repeatable multi-model critique workflow without manual copy-paste across chats
By the numbers
- Server version 0.1.12
- 1 npm package @samoradc/tetrad
- 4-model consensus positioning (quadruple consensus with Codex, Gemini, and Qwen)
README.md
Tetrad
Quadruple Consensus MCP Server for Claude Code
Tetrad is a high-performance MCP (Model Context Protocol) server written in Rust that orchestrates three AI-powered CLI code evaluation tools (Codex, Gemini CLI, Qwen) to validate all code produced by Claude Code.
The system implements a quadruple consensus protocol where no code or plan is accepted without approval from four intelligences: the three external evaluators + Claude Code itself.
Features
- Quadruple Consensus: 4 AI models must agree to approve code
- ReasoningBank: Continuous learning system with RETRIEVE→JUDGE→DISTILL→CONSOLIDATE cycle
- High Performance: Written in Rust with parallel execution via Tokio
- MCP Server: JSON-RPC 2.0 server over stdio for Claude Code integration
- Full CLI: Intuitive commands (
init,serve,status,doctor,config, etc.) - LRU Cache: Result caching with configurable TTL
- Hook System: Pre/post evaluation callbacks for customization
- Extensible: Plugin system for custom executors
- Cross-session: SQLite persistence for patterns and history
Quick Start
1. Install Tetrad
# Via npm (recommended - works seamlessly with Claude Code)
npm install -g @samoradc/tetrad
# Or via cargo (requires additional setup)
cargo install tetrad
sudo cp ~/.cargo/bin/tetrad /usr/local/bin/
1.1 Initialize in Your Project (Optional)
npx @samoradc/tetrad init
This will:
- Create
tetrad.tomlconfiguration file - Create
.tetrad/directory for the database - Add
.tetrad/to your.gitignore
2. Install and Configure External CLI Tools
Tetrad requires at least one of the following AI CLI tools. Good news: you don't need separate API keys if you have existing subscriptions!
Codex CLI (OpenAI)
npm install -g @openai/codex
Authentication options:
| Method | Requirements | API Key Needed? |
|---|---|---|
| ChatGPT Login | ChatGPT Plus, Pro, Business, Edu, or Enterprise subscription | No |
| API Key | OpenAI API account with credits | Yes |
# Option 1: Login with your ChatGPT subscription (recommended)
codex login
# Opens browser for OAuth - follow the prompts
# Option 2: Use API key
export OPENAI_API_KEY="your-openai-key"
Note: For headless/remote servers, use
codex login --device-authand follow the device code flow.
📖 Codex CLI Authentication Docs
Gemini CLI (Google)
npm install -g @google/gemini-cli
Authentication options:
| Method | Requirements | API Key Needed? | Free Tier |
|---|---|---|---|
| Google Login | Personal Google account | No | 60 req/min, 1,000 req/day |
| API Key | Google AI Studio account | Yes | Same limits |
# Option 1: Login with Google account (recommended)
gemini auth login
# Opens browser for OAuth - follow the prompts
# Option 2: Use API key from Google AI Studio
export GEMINI_API_KEY="your-gemini-key"
Free Tier: With a personal Google account, you get access to Gemini 2.5 Pro with 1M token context window at no cost!
📖 Gemini CLI Authentication Docs
Qwen CLI (Alibaba)
npm install -g qwen-code
Authentication options:
| Method | Requirements | API Key Needed? | Free Tier |
|---|---|---|---|
| DashScope API | Alibaba Cloud account | Yes | 2,000 req/day |
| Coding Plan | Qwen Coding subscription | Yes (different format) | Included |
# Get your API key from DashScope console
export DASHSCOPE_API_KEY="your-dashscope-key"
# For international users (outside China)
export OPENAI_BASE_URL="https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
Regional Endpoints:
- Singapore:
dashscope-intl.aliyuncs.com- Virginia:
dashscope-us.aliyuncs.com- Beijing:
dashscope.aliyuncs.com
3. Verify Installation
# Check Tetrad version
tetrad version
# Check CLI availability
tetrad status
# Diagnose any issues
tetrad doctor
4. Add to Claude Code CLI
# Add Tetrad as MCP server (all projects)
claude mcp add --scope user tetrad -- npx @samoradc/tetrad serve
# Verify it's configured
claude mcp list
Alternative installation methods
# Current project only
claude mcp add tetrad -- npx @samoradc/tetrad serve
# If installed via cargo
claude mcp add --scope user tetrad -- tetrad serve
Note: Tetrad is published on the MCP Registry for discoverability and documentation.
5. Alternative: Manual Configuration
Create or edit .mcp.json in your project root:
{
"mcpServers": {
"tetrad": {
"type": "stdio",
"command": "npx",
"args": ["@samoradc/tetrad", "serve"],
"env": {
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"GOOGLE_API_KEY": "${GOOGLE_API_KEY}",
"DASHSCOPE_API_KEY": "${DASHSCOPE_API_KEY}"
}
}
}
}
Or for global user configuration in ~/.claude.json (mcpServers section):
{
"mcpServers": {
"tetrad": {
"type": "stdio",
"command": "npx",
"args": ["@samoradc/tetrad", "serve"]
}
}
}
How It Works
When you ask Claude Code to write code, Tetrad automatically validates it:
You: "Create a function in Rust that calculates the average of a vector"
Claude Code:
1. Writes the code
2. Calls tetrad_review_code automatically
3. Tetrad sends to Codex, Gemini and Qwen for evaluation
4. Returns consolidated consensus from all 3 evaluators
Tetrad Response:
┌─────────────────────────────────────────────┐
│ DECISION: PASS ✓ │
│ Score: 92/100 │
│ Consensus: Yes (3/3 approved) │
│ │
│ Votes: │
│ • Codex: Pass (95) │
│ • Gemini: Pass (90) │
│ • Qwen: Pass (92) │
│ │
│ Suggestions: │
│ - Consider handling empty vector case │
└─────────────────────────────────────────────┘
Claude Code: Saves the approved code
When Issues Are Found:
Tetrad Response:
┌─────────────────────────────────────────────┐
│ DECISION: BLOCK ✗ │
│ Score: 26/100 │
│ Consensus: Yes (3/3 rejected) │
│ │
│ Votes: │
│ • Codex: Fail (30) - division by zero │
│ • Gemini: Fail (25) - no error handling │
│ • Qwen: Fail (25) - unsafe operation │
│ │
│ Issues: │
│ - Division by zero not handled │
│ - Missing input validation │
│ - No Result/Option return type │
└─────────────────────────────────────────────┘
Claude Code: Fixes the code and resubmits
CLI Commands
tetrad - Quadruple Consensus CLI for Claude Code
COMMANDS:
init Initialize configuration in current directory
serve Start the MCP server (used by Claude Code)
status Show CLI status (codex, gemini, qwen)
config Configure options interactively
doctor Diagnose configuration issues
version Show version
evaluate Evaluate code manually (without MCP)
history Show evaluation history from ReasoningBank
export Export patterns from ReasoningBank
import Import patterns into ReasoningBank
OPTIONS:
-c, --config <FILE> Configuration file (default: tetrad.toml)
-v, --verbose Verbose mode
-q, --quiet Quiet mode
-h, --help Show help
MCP Tools
When running as MCP server, Tetrad exposes 6 tools:
| Tool | Description |
|---|---|
tetrad_review_plan |
Review implementation plans before coding |
tetrad_review_code |
Review code before saving |
tetrad_review_tests |
Review tests before finalizing |
tetrad_confirm |
Confirm agreement with received feedback |
tetrad_final_check |
Final verification before commit |
tetrad_status |
Check health of evaluators |
Workflow Example
1. Claude Code generates plan → tetrad_review_plan → Feedback
2. Claude Code implements → tetrad_review_code → Feedback
3. Claude Code adjusts → tetrad_confirm → Confirmation
4. Claude Code finalizes → tetrad_final_check → Certificate
Architecture
Claude Code → MCP Protocol (stdio) → Tetrad Server (Rust)
│
┌─────────────────────┼─────────────────────┐
▼ ▼ ▼
Codex CLI Gemini CLI Qwen CLI
(syntax) (architecture) (logic)
│ │ │
└─────────────────────┼─────────────────────┘
▼
Consensus Engine
│
┌─────────────┴─────────────┐
▼ ▼
LRU Cache ReasoningBank
(results) (SQLite)
RETRIEVE→JUDGE→DISTILL→CONSOLIDATE
Executor Specializations
| Executor | CLI | Specialization |
|---|---|---|
| Codex | codex exec --json |
Syntax and code conventions |
| Gemini | gemini -o json |
Architecture and design |
| Qwen | qwen |
Logic bugs and correctness |
Consensus Rules
| Rule | Requirement | Use Case |
|---|---|---|
| Golden | Unanimity (3/3) | Critical code, security |
| Strong | 3/3 or 2/3 with high confidence | Default |
| Weak | Simple majority (2/3) | Rapid prototyping |
ReasoningBank
The ReasoningBank is a continuous learning system that stores and consolidates code patterns:
Learning Cycle
RETRIEVE → JUDGE → DISTILL → CONSOLIDATE
│ │ │ │
│ │ │ └─ Merge similar patterns
│ │ └─ Extract new patterns
│ └─ Evaluate code with context
└─ Search for relevant patterns
Pattern Types
- AntiPattern: Patterns to avoid (bugs, vulnerabilities, code smells)
- GoodPattern: Patterns to follow (best practices, idiomatic patterns)
- Ambiguous: Patterns with uncertain classification (needs more data)
ReasoningBank Commands
# View evaluation history
tetrad history --limit 50
# Export patterns to share
tetrad export -o team-patterns.json
# Import patterns from another ReasoningBank
tetrad import team-patterns.json
Configuration
The tetrad.toml file is created automatically with tetrad init:
[general]
log_level = "info"
timeout_secs = 60
[executors.codex]
enabled = true
command = "codex"
args = ["exec", "--json"]
timeout_secs = 30
[executors.gemini]
enabled = true
command = "gemini"
args = ["-o", "json"]
timeout_secs = 30
[executors.qwen]
enabled = true
command = "qwen"
args = []
timeout_secs = 30
[consensus]
default_rule = "strong"
min_score = 70
max_loops = 3
[reasoning]
enabled = true
db_path = ".tetrad/tetrad.db"
max_patterns_per_query = 10
consolidation_interval = 100
[cache]
enabled = true
capacity = 1000
ttl_secs = 300
Interactive Configuration
Use tetrad config for interactive configuration:
🔧 Tetrad Interactive Configuration
What would you like to configure?
❯ General Settings
Executors (Codex, Gemini, Qwen)
Consensus
ReasoningBank
Save and Exit
Exit without Saving
LRU Cache
The system includes an LRU cache to avoid unnecessary re-evaluations:
- Capacity: Configurable (default: 1000 entries)
- TTL: Configurable time-to-live (default: 5 minutes)
- Key: Hash of code + language + evaluation type
- Invalidation: Automatic by TTL or manual
Hook System
Hooks allow customizing behavior at specific points:
| Hook | When | Use |
|---|---|---|
pre_evaluate |
Before evaluation | Modify request, skip evaluation |
post_evaluate |
After evaluation | Logging, metrics, notifications |
on_consensus |
When consensus reached | Automatic actions on approval |
on_block |
When code blocked | Alerts, automatic rollback |
Built-in Hooks
- LoggingHook: Records all evaluations
- MetricsHook: Collects usage statistics
Project Structure
tetrad/
├── Cargo.toml # Crate manifest
├── CLAUDE.md # Documentation for Claude Code
├── README.md # This file
├── Tetrad.md # Complete specification
├── src/
│ ├── main.rs # Entry point (CLI)
│ ├── lib.rs # Exportable library
│ ├── cli/
│ │ ├── mod.rs # CLI definition with clap
│ │ ├── commands.rs # Command implementations
│ │ └── interactive.rs # Interactive configuration (dialoguer)
│ ├── executors/
│ │ ├── mod.rs
│ │ ├── base.rs # CliExecutor trait
│ │ ├── codex.rs # Codex executor
│ │ ├── gemini.rs # Gemini executor
│ │ └── qwen.rs # Qwen executor
│ ├── types/
│ │ ├── mod.rs
│ │ ├── config.rs # TOML configuration
│ │ ├── errors.rs # TetradError/TetradResult
│ │ ├── requests.rs # EvaluationRequest
│ │ └── responses.rs # EvaluationResult, ModelVote
│ ├── consensus/
│ │ ├── mod.rs # Exports
│ │ ├── engine.rs # ConsensusEngine
│ │ ├── aggregator.rs # Vote aggregation
│ │ └── rules.rs # Voting rules
│ ├── reasoning/
│ │ ├── mod.rs # Exports
│ │ ├── bank.rs # ReasoningBank
│ │ ├── patterns.rs # Pattern types
│ │ ├── sqlite.rs # SQLite storage
│ │ └── export.rs # Import/Export
│ ├── mcp/
│ │ ├── mod.rs # Exports
│ │ ├── server.rs # MCP server
│ │ ├── protocol.rs # JSON-RPC types
│ │ ├── tools.rs # Tool handlers
│ │ └── transport.rs # Stdio transport
│ ├── cache/
│ │ ├── mod.rs # Exports
│ │ └── lru.rs # LRU cache
│ └── hooks/
│ ├── mod.rs # Hook trait and HookSystem
│ └── builtin.rs # Default hooks
└── tests/
├── cli_integration.rs
├── consensus_integration.rs
├── mcp_integration.rs
└── reasoning_integration.rs
Development
# Build
cargo build
cargo build --release
# Tests
cargo test # All tests
cargo test --lib # Unit tests only
cargo test --tests # Integration tests only
# Lint
cargo clippy --all-targets --all-features -- -D warnings
# Format
cargo fmt
cargo fmt --check
# Documentation
cargo doc --open
# Run CLI
cargo run -- status
cargo run -- doctor
cargo run -- version
cargo run -- config
Troubleshooting
"CLI not found"
# Check if CLIs are in PATH
which codex
which gemini
which qwen
# Check configuration
tetrad doctor
"stdin is not a terminal" (Codex)
Make sure your config uses exec --json:
[executors.codex]
args = ["exec", "--json"]
"Response does not contain valid JSON" (Gemini)
Make sure your config uses -o json:
[executors.gemini]
args = ["-o", "json"]
Check MCP status in Claude Code
Inside Claude Code, run:
/mcp
Prerequisites
To use Tetrad, you need at least one of the AI CLIs installed and authenticated:
| CLI | Installation | Auth Without API Key? | Free Tier |
|---|---|---|---|
| Codex CLI | npm i -g @openai/codex |
✅ ChatGPT Plus/Pro/Business | Via subscription |
| Gemini CLI | npm i -g @google/gemini-cli |
✅ Google account | 1,000 req/day |
| Qwen CLI | npm i -g qwen-code |
❌ DashScope key required | 2,000 req/day |
Check availability with:
tetrad status
tetrad doctor
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
License
MIT
Author
SamoraDC
Links:
Recommended MCP Servers
How it compares
Multi-LLM consensus MCP validator, not a unit-test runner or static analyzer skill.
FAQ
Who is Tetrad for?
Tetrad is for developers and small teams who want several large models to independently judge the same code change through one MCP server.
When should I use Tetrad?
Use it in the ship and review step when a change is merge-ready but you want extra model diversity on correctness, safety, or API misuse before you commit.
How do I add Tetrad to my agent?
Install @samoradc/tetrad from npm, configure provider credentials per the GitHub repo, and register the stdio MCP server in Claude Code, Cursor, or your MCP client.