AI Consensus

Make AI Consensus astanding part of your development model. Your coding agent — Claude Code, Cursor, Cline, any MCP client — routes every decision of consequence through three frontier AIs (Claude, GPT, Gemini) that answerindependently, thencross-examine each other, and return one recommendationplus the strongest dissent. You keep working inside your agent; the panel reviews as you go.

This is not a tool you reach for occasionally. It's a review layer you switch on once, and from then on everything that matters gets debated by three independent models before it ships. (Honest bill: a run takes a few minutes and, on the bring-your-own-keys plan, costs roughly $0.40–$1 of your own provider tokens.)

claude mcp add ai-consensus --scope user \ --env AI_CONSENSUS_API_KEY=aic_live_your_key_here \ -- npx -y ai-consensus-connector

(Self-hosting? add--env AI_CONSENSUS_API_URL=https://your-instance.)

Verify it's connected (free — no run is started):

"Use the check_ai_consensus_connection tool."

Make it your standing rule — add to your project'sCLAUDE.md:

STANDING RULE: This project develops with AI Consensus as its review layer. Route every decision of consequence — architecture, design, implementation approach, tricky bugs, anything whose cost of being wrong is real — through consult_ai_consensus as a matter of course, and weigh its recommendation and strongest dissent before acting. Purely mechanical edits (formatting, typos, exact instructed changes) don't need a run. When in doubt, consult.

Teams that wanteverythingrouted can use the strict variant instead:

STRICT MODE: Consult consult_ai_consensus before every non-trivial change of any kind, and weigh the dissent before acting.

Setup — Cursor / Cline / other MCP clients

Add a stdio MCP server with commandnpx -y ai-consensus-connectorand theAI_CONSENSUS_API_KEYenvironment variable. For Cursor, inmcp.json:

{ "mcpServers": { "ai-consensus": { "command": "npx", "args": ["-y", "ai-consensus-connector"], "env": { "AI_CONSENSUS_API_KEY": "aic_live_your_key_here" } } } }

Then put the standing rule in your project's agent rules file (.cursorrules,.clinerules, etc.).

- consult_ai_consensus— route a decision/task through the panel and wait for the result (a few minutes).
- start_ai_consensus/get_ai_consensus_result— fire-and-forget + collect later.
- check_ai_consensus_connection— zero-cost setup check (reachability, key accepted, provider keys present).
- cancel_ai_consensus_run— stop a run.

Your key authenticates to your account and bills your plan (unlimited on your own keys, or prepaid credits). Keep it secret — and note that pasting the--envform above stores the key in your shell history; use your client's config file if that concerns you.

This connector is open source under theMIT license. It is a thin client for thepaid, hosted AI Consensus service— you bring your own AI Consensus API key; the deliberation engine itself runs on our servers and is not part of this repository. The MIT license covers this connector's code only and grants no rights to the AI Consensus name or branding.

Support boundary:connector bugs and setup issues →GitHub issues; account, API-key or billing questions →support@ai-consensus.ai.

Stop AI Hallucinations Before They Start Run models from OpenAI, Google, Anthropic, xAI, Perplexity, and OpenRouter in parallel. They check each other's work, debate solutions, and catch errors before you see them.