MCP MeasureMCP Measure

index observed

What's That Model?

Sourced AI video/image capabilities, explained task recommendations and verified access context.

Should I use this

Quality & Safety

A
Description quality
90%
Schema completeness
71%
Naming quality
93%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Findings (2)

  • LOWTool 'compare_models' description lacks action verbin compare_models
  • LOWTool 'where_to_use' description lacks action verbin where_to_use

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~927Tokens (tool definitions)
~769 BTypical response size
Moderate attention impact (0.72% 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": {
    "whats-that-model": {
      "url": "https://whatsthatmodel.com/mcp"
    }
  }
}

Remote endpoints

https://whatsthatmodel.com/mcpstreamable-http

What it can do

Tool inventory

Tools (8)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢find_model(task, constraints)

Find an AI model by creation task and verified constraints. Editorial recommendation; not a benchmark score.

Input Schema

{
  "type": "object",
  "properties": {
    "task": {
      "type": "string",
      "enum": [
        "ai-influencer",
        "ai-video-generator",
        "character-consistency",
        "cinematic-video",
        "image-to-video",
        "product-shots",
        "product-videos",
        "realistic-humans",
        "social-shorts",
        "talking-characters",
        "text-in-images",
        "ugc-ads"
      ]
    },
    "constraints": {
      "type": "object",
      "properties": {
        "output": {
          "type": "string",
          "enum": [
            "video",
            "image",
            "any"
          ]
        },
        "input": {
          "type": "string",
          "enum": [
            "text",
            "image",
            "video",
            "youtube"
          ]
        },
        "audio": {
          "type": "boolean"
        },
        "duration": {
          "type": "number",
          "minimum": 1
        },
        "budget": {
          "type": "string",
          "enum": [
            "draft",
            "flexible"
          ]
        },
        "style": {
          "type": "string",
          "enum": [
            "realistic",
            "cinematic",
            "stylized"
          ]
        },
        "platform": {
          "type": "string",
          "enum": [
            "portrait",
            "landscape",
            "any"
          ]
        }
      },
      "additionalProperties": false
    }
  },
  "additionalProperties": false
}
🟢compare_models(models, task)

Compare documented capabilities and task fit. Unknowns stay explicit.

Input Schema

{
  "type": "object",
  "properties": {
    "models": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "minItems": 2,
      "maxItems": 4
    },
    "task": {
      "type": "string"
    }
  },
  "required": [
    "models"
  ],
  "additionalProperties": false
}
🟢get_model(model)

Get model capabilities, dated citations, editorial limitations and labeled optional access link.

Input Schema

{
  "type": "object",
  "properties": {
    "model": {
      "type": "string"
    }
  },
  "required": [
    "model"
  ],
  "additionalProperties": false
}
🟢best_model_for(use_case, constraints)

Get an editorial shortlist for a known use case with verified constraints.

Input Schema

{
  "type": "object",
  "properties": {
    "use_case": {
      "type": "string",
      "enum": [
        "ai-influencer",
        "ai-video-generator",
        "character-consistency",
        "cinematic-video",
        "image-to-video",
        "product-shots",
        "product-videos",
        "realistic-humans",
        "social-shorts",
        "talking-characters",
        "text-in-images",
        "ugc-ads"
      ]
    },
    "constraints": {
      "type": "object"
    }
  },
  "required": [
    "use_case"
  ],
  "additionalProperties": false
}
🟢list_models(filters)

List curated AI models including independent non-affiliate alternatives.

Input Schema

{
  "type": "object",
  "properties": {
    "filters": {
      "type": "object",
      "properties": {
        "kind": {
          "type": "string",
          "enum": [
            "video",
            "image",
            "tool"
          ]
        },
        "audio": {
          "type": "boolean"
        },
        "higgsfield": {
          "type": "boolean"
        },
        "image_to_video": {
          "type": "boolean"
        },
        "min_duration": {
          "type": "number"
        }
      },
      "additionalProperties": false
    }
  },
  "additionalProperties": false
}
🟢where_to_use(model)

Return official and optional commercial access destinations, without guaranteeing plan entitlements.

Input Schema

{
  "type": "object",
  "properties": {
    "model": {
      "type": "string"
    }
  },
  "required": [
    "model"
  ],
  "additionalProperties": false
}
🟢get_trending_workflows

Get curated workflow spotlights; no unmeasured growth or income claims.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_prompt_tips(model, task)

Get untested prompting guidance, clearly distinguished from measured outputs.

Input Schema

{
  "type": "object",
  "properties": {
    "model": {
      "type": "string"
    },
    "task": {
      "type": "string"
    }
  },
  "required": [
    "model"
  ],
  "additionalProperties": false
}

Community

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Evidence

Recent observations

verifiedversion not recorded8 tools