OpenClaw Consensus
Query nine LLMs for consensus and disagreement scores so you trust agent answers before you build on them.
Overview
OpenClaw Consensus is a MCP server for the Validate phase that runs 9-LLM consensus with disagreement scoring and cheapest-route routing.
What is this MCP server?
- 9-LLM consensus aggregation with explicit disagreement scoring
- Cheapest-route model selection to control API spend on multi-model runs
- Designed to reduce hallucination risk on critical questions
- PyPI openclaw-consensus-mcp v0.1.1 with stdio transport
- Requires RAPIDAPI_KEY from RapidAPI OpenClaw Consensus API
- 9-LLM consensus design stated in server description
- Server version 0.1.1 on PyPI identifier openclaw-consensus-mcp
- stdio transport; repository github.com/MICONNM/openclaw-consensus-mcp
What problem does it solve?
A single coding agent can sound confident while wrong, and you have no fast way to see if other models agree.
Who is it for?
Indie builders validating stack, legal-ish, or market claims from agents when wrong answers would waste weeks of build time.
Skip if: Routine codegen with local tests, or teams barred from sending prompts to third-party multi-LLM APIs.
What do I get? / Deliverables
After setup, you get multi-model consensus and disagreement scores so shaky agent claims surface before you commit scope or ship.
- Consensus result across up to nine LLMs on a posed question
- Disagreement scoring to flag unstable answers
- Cost-optimized model route selection for the consensus call
Recommended MCP Servers
Journey fit
How it compares
Multi-LLM consensus MCP service, not a local linter or single-provider chat skill.
Common Questions / FAQ
Who is OpenClaw Consensus for?
Solo builders using MCP agents who want a second line of defense via nine-model agreement before trusting high-stakes answers.
When should I use OpenClaw Consensus?
Use it when scoping product decisions, validating facts, or reviewing agent-generated guidance where hallucinations would be costly.
How do I add OpenClaw Consensus to my agent?
Install PyPI package openclaw-consensus-mcp (stdio), set RAPIDAPI_KEY from rapidapi.com/yanmiayn/api/openclaw-consensus, and register the server in your MCP client.