MCP MeasureMCP Measure

index observed

AI Recommendation Readiness Audit | The Black Friday Agency

Can AI confidently recommend your business? The AI Recommendation Readiness Audit shows whether your

Should I use this

Quality & Safety

A
Description quality
100%
Schema completeness
65%
Naming quality
90%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Findings (1)

  • LOWTool 'assess_ai_recommendation_readiness' name length outside 3-30 rangein assess_ai_recommendation_readiness

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~1,344Tokens (tool definitions)
~7.9 KBTypical response size
Moderate attention impact (1.05% 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": {
    "canairecommendmybusiness-com": {
      "url": "https://canairecommendmybusiness.com/api/mcp"
    }
  }
}

Remote endpoints

https://canairecommendmybusiness.com/api/mcpstreamable-http

What it can do

Tool inventory

Tools (2)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢assess_ai_recommendation_readiness(businessSize, dataMaturity, technicalStack, goals, businessName, ...)

Assesses whether a business is ready to be understood, verified, trusted, recommended, and used by AI systems, based on structured inputs (business size, data availability/maturity, technical stack/infrastructure, and goals). Returns a readiness score, tier, gap analysis, priority actions, and a phased implementation roadmap. Deterministic and read-only: it performs no consequential actions and does not guarantee any ranking or recommendation.

Input Schema

{
  "type": "object",
  "properties": {
    "businessSize": {
      "type": "string",
      "enum": [
        "solo",
        "micro",
        "small",
        "midmarket",
        "enterprise"
      ],
      "description": "Size of the business/organization."
    },
    "dataMaturity": {
      "type": "string",
      "enum": [
        "none",
        "basic",
        "developing",
        "structured",
        "advanced"
      ],
      "description": "Availability and maturity of the structured/machine-readable data of the business."
    },
    "technicalStack": {
      "type": "string",
      "enum": [
        "minimal",
        "standard",
        "modern",
        "advanced"
      ],
      "description": "Technical stack / infrastructure sophistication."
    },
    "goals": {
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "ai_visibility",
          "lead_generation",
          "trust_authority",
          "content_coverage",
          "conversion_optimization",
          "structured_data",
          "agent_readiness",
          "reputation_management"
        ]
      },
      "minItems": 1,
      "maxItems": 8,
      "uniqueItems": true,
      "default": [
        "ai_visibility"
      ],
      "description": "One or more readiness goals the business wants to prioritize (1–8, unique values from the enum)."
    },
    "businessName": {
      "type": "string",
      "description": "Optional, non-sensitive business name for context."
    },
    "industry": {
      "type": "string",
      "description": "Optional industry/category for context."
    }
  },
  "required": [
    "businessSize",
    "dataMaturity",
    "technicalStack"
  ]
}

Output Schema

{
  "type": "object",
  "properties": {
    "tool": {
      "type": "string",
      "description": "Canonical tool identifier."
    },
    "engineVersion": {
      "type": "string",
      "description": "Version of the deterministic scoring engine."
    },
    "readinessScore": {
      "type": "number",
      "minimum": 0,
      "maximum": 100,
      "description": "Overall AI recommendation readiness score (0–100)."
    },
    "tier": {
      "type": "object",
      "properties": {
        "level": {
          "type": "integer",
          "minimum": 1,
          "maximum": 4,
          "description": "Tier level (1–4)."
        },
        "name": {
          "type": "string",
          "enum": [
            "Foundational",
            "Developing",
            "Established",
            "Optimized"
          ],
          "description": "Readiness tier name."
        },
        "summary": {
          "type": "string",
          "description": "Plain-language summary of the tier."
        }
      },
      "required": [
        "level",
        "name",
        "summary"
      ],
      "additionalProperties": false
    },
    "dimensionScores": {
      "type": "array",
      "description": "Per-dimension breakdown of the overall score.",
      "items": {
        "type": "object",
        "properties": {
          "key": {
            "type": "string",
            "description": "Dimension identifier."
          },
          "label": {
            "type": "string",
            "description": "Human-readable dimension name."
          },
          "score": {
            "type": "number",
            "minimum": 0,
            "maximum": 100,
            "description": "Dimension score (0–100)."
          },
          "weight": {
            "type": "number",
            "minimum": 0,
            "maximum": 1,
            "description": "Weight of this dimension in the overall score."
          }
        },
        "required": [
          "key",
          "label",
          "score",
          "weight"
        ],
        "additionalProperties": true
      }
    },
    "gapAnalysis": {
      "type": "array",
      "description": "Identified gaps between current and target readiness.",
      "items": {
        "type": "object",
        "properties": {
          "area": {
            "type": "string",
            "description": "Gap area / dimension."
          },
          "severity": {
            "type": "string",
            "enum": [
              "low",
              "moderate",
              "high",
              "critical"
            ],
            "description": "Severity of the gap."
          },
          "description": {
            "type": "string",
            "description": "Explanation of the gap."
          }
        },
        "required": [
          "area",
          "severity",
          "description"
        ],
        "additionalProperties": true
      }
    },
    "priorityActions": {
      "type": "array",
      "description": "Prioritized recommended actions.",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string",
            "description": "Short action title."
          },
          "detail": {
            "type": "string",
            "description": "Action detail / rationale."
          },
          "effort": {
            "type": "string",
            "enum": [
              "low",
              "medium",
              "high"
            ],
            "description": "Estimated effort."
          },
          "impact": {
            "type": "string",
            "enum": [
              "low",
              "medium",
              "high"
            ],
            "description": "Estimated impact."
          }
        },
        "required": [
          "title"
        ],
        "additionalProperties": true
      }
    },
    "implementationRoadmap": {
      "type": "array",
      "description": "Phased implementation roadmap.",
      "items": {
        "type": "object",
        "properties": {
          "phase": {
            "type": "string",
            "description": "Phase name."
          },
          "focus": {
            "type": "string",
            "description": "Primary focus of the phase."
          },
          "actions": {
            "type": "array",
            "items": {
              "type": "string"
            },
            "description": "Actions within the phase."
          }
        },
        "required": [
          "phase"
        ],
        "additionalProperties": true
      }
    },
    "normalizedInputs": {
      "type": "object",
      "description": "The normalized inputs actually used for scoring.",
      "properties": {
        "businessSize": {
          "type": "string"
        },
        "dataMaturity": {
          "type": "string"
        },
        "technicalStack": {
          "type": "string"
        },
        "goals": {
          "type": "array",
          "items": {
            "type": "string"
          }
        }
      },
      "additionalProperties": true
    },
    "disclaimer": {
      "type": "string",
      "description": "Educational-use disclaimer."
    }
  },
  "required": [
    "readinessScore",
    "tier",
    "dimensionScores",
    "gapAnalysis",
    "priorityActions",
    "normalizedInputs",
    "disclaimer"
  ],
  "additionalProperties": true
}
🟢get_ai_readiness_framework

Returns the AI Recommendation Readiness scoring framework: the scored dimensions and their weights, the four readiness tiers with score ranges, and every valid input option (business sizes, data maturity levels, technical stacks, and goals). Read-only and deterministic; use it to understand how the assessment is scored and to build valid inputs for assess_ai_recommendation_readiness.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}

Output Schema

{
  "type": "object",
  "properties": {
    "engineVersion": {
      "type": "string"
    },
    "dimensions": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "key": {
            "type": "string"
          },
          "label": {
            "type": "string"
          },
          "weight": {
            "type": "number",
            "minimum": 0,
            "maximum": 1
          }
        },
        "required": [
          "key",
          "label",
          "weight"
        ],
        "additionalProperties": false
      }
    },
    "tiers": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "level": {
            "type": "integer",
            "minimum": 1,
            "maximum": 4
          },
          "name": {
            "type": "string"
          },
          "scoreRange": {
            "type": "string"
          }
        },
        "required": [
          "level",
          "name",
          "scoreRange"
        ],
        "additionalProperties": false
      }
    },
    "inputOptions": {
      "type": "object",
      "properties": {
        "businessSize": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "dataMaturity": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "technicalStack": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "goals": {
          "type": "array",
          "items": {
            "type": "string"
          }
        }
      },
      "required": [
        "businessSize",
        "dataMaturity",
        "technicalStack",
        "goals"
      ],
      "additionalProperties": false
    },
    "disclaimer": {
      "type": "string"
    }
  },
  "required": [
    "engineVersion",
    "dimensions",
    "tiers",
    "inputOptions",
    "disclaimer"
  ],
  "additionalProperties": false
}

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Evidence

Recent observations

verifiedversion not recorded2 tools
verifiedversion not recorded2 tools