mcp

See how ChatGPT, Claude, Perplexity, and Gemini cite brands, prompts, and sources.

Should I use this

Quality & Safety

A
Description quality
90%
Schema completeness
72%
Naming quality
100%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~446Tokens (tool definitions)
~310 BTypical response size
Minimal attention impact (0.35% 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": {
    "mcp": {
      "command": "npx",
      "args": [
        "@parse-gl/mcp"
      ]
    }
  }
}

Runnable packages

npm@parse-gl/mcp1.0.0stdio

Remote endpoints

https://mcp.parse.gl/mcpstreamable-http

What it can do

Tool inventory

Tools (6)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢parse_search(query, types, limit)

Find brands, organic AI prompts, and market niches for marketer research. Use this first when the user names a brand, category, or AI visibility question.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    },
    "types": {
      "type": "array",
      "items": {
        "type": "string",
        "enum": [
          "brands",
          "prompts",
          "niches"
        ]
      }
    },
    "limit": {
      "type": "number",
      "minimum": 1,
      "maximum": 10
    }
  },
  "required": [
    "query"
  ]
}
🟢parse_get_brand(slug_or_id)

Fetch a concise public marketing brief for one brand, including Parse score, strengths, weak spots, top prompts, citation sources, related brands, and next research questions.

Input Schema

{
  "type": "object",
  "properties": {
    "slug_or_id": {
      "type": "string"
    }
  },
  "required": [
    "slug_or_id"
  ]
}
🟢parse_get_prompt(slug)

Fetch one public organic prompt by slug when the user wants to inspect the exact AI-search question behind a result.

Input Schema

{
  "type": "object",
  "properties": {
    "slug": {
      "type": "string"
    }
  },
  "required": [
    "slug"
  ]
}
🟢parse_get_stats

Explain the public Parse index scale and freshness: tracked brands, organic prompts, and citation observations.

Input Schema

{
  "type": "object",
  "properties": {}
}
🟢search(query, limit)

Compatibility alias for parse_search. Use for clients that expect a generic search tool.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string"
    },
    "limit": {
      "type": "number",
      "minimum": 1,
      "maximum": 10
    }
  },
  "required": [
    "query"
  ]
}
🟢fetch(id)

Compatibility alias that resolves fetch IDs like brand:stripe or prompt:best-crm into JSON-text results with human-readable text.

Input Schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string"
    }
  },
  "required": [
    "id"
  ]
}

Community

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Evidence

Recent observations

verifiedversion not recorded6 tools
verifiedversion not recorded6 tools