MCP MeasureMCP Measure

index observed

AIUseCaseHub

Source-linked enterprise AI deployment search. Free preview; API keys unlock full results.

Should I use this

Quality & Safety

A
Description quality
95%
Schema completeness
100%
Naming quality
90%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~754Tokens (tool definitions)
~1.9 KBTypical response size
Moderate attention impact (0.59% 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": {
    "aiusecasehub": {
      "url": "https://basic-backend713-dsd8hygyfkc8d8f5.swedencentral-01.azurewebsites.net/api/mcp"
    }
  }
}

Remote endpoints

https://basic-backend713-dsd8hygyfkc8d8f5.swedencentral-01.azurewebsites.net/api/mcpstreamable-http

What it can do

Tool inventory

Tools (4)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢search_usecases(search_term, query, limit)

Search curated AI use cases using the default hybrid ranking. Use this when an agent has a natural-language search term.

Input Schema

{
  "type": "object",
  "properties": {
    "search_term": {
      "type": "string",
      "description": "Natural-language search term."
    },
    "query": {
      "type": "string",
      "description": "Alias for search_term."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 20,
      "default": 10,
      "description": "Maximum results requested. Public previews return at most 3; personal-key access permits up to 20."
    }
  },
  "required": [
    "search_term"
  ]
}
🟢hybrid_search_usecases(query, limit, industry, country, technologies_used, ...)

Search AI use cases with hybrid full-text and vector ranking. Supports provider, industry, geography, technology, customer, partner, and boolean case-type filters.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Natural-language query."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 20,
      "default": 10,
      "description": "Maximum results requested. Public previews return at most 3; personal-key access permits up to 20."
    },
    "industry": {
      "type": "string",
      "description": "Filter by the deployment industry."
    },
    "country": {
      "type": "string",
      "description": "Filter by country code, for example US or GB."
    },
    "technologies_used": {
      "type": "string",
      "description": "Filter by technology name."
    },
    "cloud_provider": {
      "type": "string",
      "description": "Microsoft, AWS, GCP, or comma-separated values."
    },
    "customer_name": {
      "type": "string",
      "description": "Filter by the company adopting AI."
    },
    "partner_name": {
      "type": "string",
      "description": "Filter by implementation partner."
    },
    "isAgentCase": {
      "type": "boolean",
      "description": "Filter for AI agent deployments."
    },
    "isMultiAgentCase": {
      "type": "boolean",
      "description": "Filter for multi-agent deployments."
    },
    "isRag": {
      "type": "boolean",
      "description": "Filter for retrieval-augmented generation deployments."
    },
    "isVision": {
      "type": "boolean",
      "description": "Filter for computer vision deployments."
    },
    "isCopilot": {
      "type": "boolean",
      "description": "Filter for copilot deployments."
    },
    "isVoice": {
      "type": "boolean",
      "description": "Filter for voice AI deployments."
    },
    "isFineTuning": {
      "type": "boolean",
      "description": "Filter for model fine-tuning deployments."
    },
    "isMicrosoftFabric": {
      "type": "boolean",
      "description": "Filter for Microsoft Fabric deployments."
    },
    "isAvatar": {
      "type": "boolean",
      "description": "Filter for AI avatar deployments."
    },
    "isSustainabilityCase": {
      "type": "boolean",
      "description": "Filter for sustainability use cases."
    }
  },
  "required": [
    "query"
  ]
}
🟢vector_search_usecases(query, limit)

Semantic vector search for AI use cases using the meaning of the query text.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Natural-language query."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 20,
      "default": 10,
      "description": "Maximum results requested. Public previews return at most 3; personal-key access permits up to 20."
    }
  },
  "required": [
    "query"
  ]
}
🟢get_usecase_details(row_key, id)

Fetch detailed information for a single AI use case by RowKey/id.

Input Schema

{
  "type": "object",
  "properties": {
    "row_key": {
      "type": "string",
      "description": "The RowKey/id returned by search tools."
    },
    "id": {
      "type": "string",
      "description": "Alias for row_key."
    }
  },
  "required": [
    "row_key"
  ]
}

Community

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Evidence

Recent observations

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