content_similar

Active

declared in 0.2.0

Find content entities similar to a given one. For embedded franchises this uses SEMANTIC vector similarity (pgvector) over the enrichment profile — surfacing entities that feel alike even when their tags differ literally. Falls back to shared enrichment-tag overlap for works or non-embedded entities. Each result carries a similarity score and its entity-level freshness/confidence (verifiable, sourced). When to use this tool: an agent wants recommendations or lookalikes for a franchise or work. Input: an entity_id and its type.

Parameters schema

{
  "type": "object",
  "required": [
    "entity_id"
  ],
  "properties": {
    "async": {
      "type": "boolean",
      "description": "If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts."
    },
    "limit": {
      "type": "integer",
      "maximum": 30,
      "minimum": 1
    },
    "entity_id": {
      "type": "string",
      "description": "Entity id from content_catalog"
    },
    "entity_type": {
      "enum": [
        "franchise",
        "work"
      ],
      "type": "string"
    }
  }
}

What this tool wraps· 0 endpoints

min confidence0.70 0.50

No endpoints wrapped at confidence ≥ 0.70.

Parent server

gapup-mcp

https://github.com/getgapup/gapup-mcp-public

2/7 registries

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