irrational
Adversarial behavioural-bias engine — audits your decisions for cognitive biases via your own AI.
Should I use this
Quality & Safety
A
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
~348Tokens (tool definitions)
~1.0 KBTypical response size
Minimal attention impact (0.27% of 128k context)
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"irrational": {
"url": "https://irrational.pages.dev/mcp/server"
}
}
}Remote endpoints
https://irrational.pages.dev/mcp/serverstreamable-httpWhat it can do
Tool inventory
Tools (3)
🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢analyze_decision(judgment, reasoning, mode, language, structured)
Adversarially audit a decision for cognitive biases. Returns a directive YOUR model executes to produce the composed audit (verdict-first). Provide reasoning, not just the conclusion.
Input Schema
{
"type": "object",
"properties": {
"judgment": {
"type": "string",
"description": "The decision/judgment in one line."
},
"reasoning": {
"type": "string",
"description": "How you arrived at it (required to audit)."
},
"mode": {
"type": "string",
"enum": [
"forward",
"retrospective"
],
"description": "forward = a decision you are about to make; retrospective = reviewing a past decision/outcome."
},
"language": {
"type": "string",
"description": "Optional. Natural language for the audit prose (e.g. \"Tamil\", \"Spanish\"). Bias ids stay canonical English so the result is still parseable. Defaults to English."
},
"structured": {
"type": "boolean",
"description": "Optional. Default false → the audit comes back as readable prose. Set true to get a machine-parseable JSON object (bias ids/keys in English) for pipelines that store or compare audits."
}
},
"required": [
"judgment"
]
}🟢list_biases(family)
List the 22-bias catalogue, optionally filtered by family.
Input Schema
{
"type": "object",
"properties": {
"family": {
"type": "string",
"enum": [
"too-much-information",
"not-enough-meaning",
"need-to-act-fast",
"what-we-remember"
]
}
}
}🟢get_bias(id)
Get the full entry for one bias by id.
Input Schema
{
"type": "object",
"properties": {
"id": {
"type": "string"
}
},
"required": [
"id"
]
}Community
Evidence
Recent observations
verifiedversion not recorded3 tools
verifiedversion not recorded3 tools