AI Consensus MCP server
io.github.TheStevenJohnstone/ai-consensus·v0.12.2Standing review layer for coding agents: Claude, GPT and Gemini debate, return consensus + dissent.
0 stars27 downloads/wk
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If you have run it, two minutes of your experience saves the next person an afternoon.
AI Consensus tools (5, 1 write)
write = sends, deletes, buys or postsRead from the package source without running it. The installed server may list more.
cancel_ai_consensus_runwrite actionCancel an in-progress AI Consensus run by id.
check_ai_consensus_connectionZero-cost setup check: verifies the API is reachable, your AI Consensus key is accepted, and (on bring-your-own-keys plans) which provider keys are present. Does NOT start a deliberation and costs nothing. Use right after installing the connector.
consult_ai_consensusRoute a decision, question, or task through three frontier AIs (Claude, GPT, Gemini) that answer independently, then cross-examine each other — returning one recommendation plus the strongest dissent. Intended as a STANDING part of the development loop: consult it as a matter of course for any decision of consequence (architecture, design, approach, tricky bugs, anything whose cost of being wrong
get_ai_consensus_resultFetch the status/result of an AI Consensus run by id.
start_ai_consensusStart an AI Consensus run without waiting; returns a run id to collect later.
Public scan report
scanner v0.1.9 · 2026-09-25 · same rubric, same numbers if you re-run it
- Code scan2 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitystatic API keys via environment variables6/15
- Maintenancelast push 67 days ago12/15
- Maintainer identityregistry namespace matches repository owner6/10
How AI Consensus compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 75/100
- higher than 45% of 48,255 servers
- Tools
- 5
- the typical server has 7
- Tools that change things
- 20%
- typical: 0%. Fewer write tools means less an agent can break
- Downloads a week
- 27
- more than 14% of 12,191 servers with a package
What its tools let an agent do: 3 read · 1 delete · 1 run or deploy
Install AI Consensus in Claude Code, Cursor or VS Code
Runs npx -y ai-consensus-connector on your machine. Read the scan report first; the gateway never runs local packages.
claude mcp add ai-consensus -- npx -y ai-consensus-connector
What the publisher says
From the AI Consensus repository's README, as published. We do not edit it. Read it on GitHub
AI Consensus — coding-agent connector
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.
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.)
Setup — Claude Code (about 2 minutes)
- 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 AICONSENSUSAPI_URL=https://your-instance.)
- Verify it's connected (free — no run is started):
"Use the checkaiconsensus_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.Setup — Cursor / Cline / other MCP clients
Add a stdio MCP server with command npx -y ai-consensus-connector and the AICONSENSUSAPI_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.).
Tools
- consultaiconsensus — route a decision/task through the panel and wait for the result (a few minutes).
- startaiconsensus / getaiconsensus_result — fire-and-forget + collect later.
- checkaiconsensus_connection — zero-cost setup check (reachability, key accepted, provider keys present).
- cancelaiconsensus_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.
Open source, hosted service
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 → support@ai-consensus.ai.
Nothing above is checked by us. What we check is on the safety report.
AI Consensus: common questions
- Is AI Consensus MCP server safe?
- Mostly: it is graded B (75/100). Read the AI Consensus safety report
- How do I install AI Consensus?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does AI Consensus need an API key?
- Yes. The registry entry asks for
AI_CONSENSUS_API_KEY. - Is AI Consensus maintained?
- The last commit was 106 days ago (2026-07-21). The latest release is v0.12.2.
- How does AI Consensus compare with other MCP servers?
- safety score 75/100 (higher than 45% of 48,255 servers); tools 5 (the typical server has 7); tools that change things 20% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.