에이전트 강화
게시자의 자체 명령입니다. PlugMCP 엔드포인트가 아닙니다.
Host a copy with our keys and logs.
npx -y [email protected]Claude Code에는 로컬 명령용 설치 링크가 없습니다. 아래 명령을 복사해 터미널에서 실행합니다.
AI_CONSENSUS_API_KEY=<secret> claude mcp add io.github.thestevenjohnstone-ai-consensus -- npx -y ai-consensus-connector@0.12.2터미널에서 실행합니다.
{ "mcpServers": { "io.github.thestevenjohnstone-ai-consensus": { "command": "npx", "args": [ "-y", "[email protected]" ], "env": { "AI_CONSENSUS_API_KEY": "<secret>" } } }}claude_desktop_config.json
원격 URL인가요, 내 컴퓨터에서 실행하는 명령인가요? 두 설치 방식의 차이
PlugMCP에서 실행
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
실행게시자 제공
Make AI Consensus a standing 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 answer independently, then cross-examine each other, and return one recommendation plus the strongest dissent. You keep working inside your agent; the panel reviews as you go.
Standing review layer for coding agents: Claude, GPT and Gemini debate, return consensus + dissent.
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.)
Get an API key: sign in at https://ai-consensus.ai → Developer API → create a key (copy it; it's shown once).
Add the connector:
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's CLAUDE.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 want everything routed 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.
Add a stdio MCP server with command npx -y ai-consensus-connector and the
AI_CONSENSUS_API_KEY environment variable. For Cursor, in mcp.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
--env form above stores the key in your shell history; use your client's
config file if that concerns you.
This connector is open source under the MIT license. It is a thin client for the paid, 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 → [email protected].
Standing review layer for coding agents: Claude, GPT and Gemini debate, return consensus + dissent.
{ "mcpServers": { "io.github.thestevenjohnstone-ai-consensus": { "command": "npx", "args": [ "-y", "[email protected]" ], "env": { "AI_CONSENSUS_API_KEY": "<secret>" } } }}도구
아직 도구 목록이 없습니다. 원격 서버는 첫 상태 확인 후에 도구 목록이 생깁니다.
FAQ
이 페이지에서 Cursor, Claude Desktop, Claude Code 또는 VS Code용 stdio 설정을 복사합니다. PlugMCP 프록시가 아니라 게시자의 설치 방식을 사용합니다.
게시자가 등록한 환경 변수: AI_CONSENSUS_API_KEY.
Ai Consensus은(는) stdio를 통해 로컬에서 실행됩니다.
마지막 확인: 2026-11-09. Standing review layer for coding agents: Claude, GPT and Gemini debate, return consensus + dissent.