plugin.json

{
  "$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
  "name": "cafeteria",
  "version": "1.0.2",
  "description": "Organization-scoped, read-only MCP access to [cafeteria] consumer insights.",
  "author": {
    "name": "Cafeteria, Inc.",
    "email": "hello@teamcafeteria.com",
    "url": "https://www.teamcafeteria.com"
  },
  "homepage": "https://www.teamcafeteria.com",
  "keywords": [
    "consumer insights",
    "Gen Z",
    "brand mentions",
    "market research",
    "MCP"
  ],
  "extensions": {
    "com.openai": {
      "interface": {
        "displayName": "[cafeteria]",
        "shortDescription": "Gen Next consumer insights",
        "longDescription": "For brand and research teams with an authorized [cafeteria] account, [cafeteria] provides queries over consumer-insights data available to their organization. Find frequently mentioned brands and topics; analyze named entities with mention counts, demographic breakdowns, and sample responses; or run a read-only SELECT query against documented [cafeteria] tables. Access uses OAuth and is scoped server-side to the connected organization's permissions. Results depend on available data and selected filters. Direct SQL results are capped at 1,000 rows. The tools do not create, update, or delete data.",
        "developerName": "Cafeteria, Inc.",
        "category": "Data & Analytics",
        "websiteURL": "https://www.teamcafeteria.com",
        "supportURL": "https://www.teamcafeteria.com/client-faqs",
        "privacyPolicyURL": "https://www.teamcafeteria.com/privacy",
        "termsOfServiceURL": "https://www.teamcafeteria.com/terms",
        "defaultPrompt": [
          "Which sneaker brands are mentioned most by young consumers?",
          "What do respondents say about Nike and Adidas?",
          "Compare sunscreen mentions among women aged 16 to 19."
        ],
        "composerIcon": "./assets/composer-icon.png",
        "logo": "./assets/logo.png"
      },
      "review": {
        "demo_recording_url": "https://cafeteria-review-media.s3.us-east-1.amazonaws.com/openai-review/bd7e93b815bd7cd35fe2518eb79c814a/cafeteria-openai-demo.mp4",
        "test_cases": {
          "positive": [
            {
              "description": "Discover highly mentioned entities for a broad topic.",
              "prompt": "Which sneaker brands are mentioned most by young consumers?",
              "tools_triggered": "top_entities",
              "expected_behavior": "Search broadly for sneaker-related entities and return ranked terms with mention and unique-user counts. If no matches are found, explain that the filters may be too narrow rather than calling it a database failure."
            },
            {
              "description": "Apply supported gender and age filters during entity discovery.",
              "prompt": "Which sunscreen brands are mentioned most by women aged 16 to 19?",
              "tools_triggered": "top_entities",
              "expected_behavior": "Use the sunscreen query with the female gender filter and inclusive ages 16 through 19. Return the ranked results and counts, or explain if no matching data is available."
            },
            {
              "description": "Compare named brands using counts, demographics, and sample responses.",
              "prompt": "What do respondents say about Nike and Adidas? Compare their mentions and sample comments.",
              "tools_triggered": "mention_count",
              "expected_behavior": "Analyze Nike and Adidas together and report the available mention counts, unique-user counts, demographic breakdowns, and sample responses for each."
            },
            {
              "description": "Apply a supported geographic filter to a named-entity analysis.",
              "prompt": "How is Nike discussed in California? Include the demographic breakdown and sample responses.",
              "tools_triggered": "mention_count",
              "expected_behavior": "Analyze Nike with California as the state filter. Report the returned counts, demographic breakdown, and sample responses without claiming broader geographic coverage than the result supports."
            },
            {
              "description": "Run a documented read-only query against the brand catalog.",
              "prompt": "Show me ten brand names and their categories from the [cafeteria] catalog.",
              "tools_triggered": "query_cafeteria_tables",
              "expected_behavior": "Use a single SELECT on studio_production.brands for name and category, with a limit of ten rows. Return only rows available to the authenticated organization."
            }
          ],
          "negative": [
            {
              "description": "Do not invoke a tool for a destructive request; explain that the available database access is read-only.",
              "prompt": "Delete all records mentioning Nike from the [cafeteria] database."
            },
            {
              "description": "Do not attempt to bypass organization isolation; explain that access is restricted to the authenticated organization's data.",
              "prompt": "Query another [cafeteria] customer's responses by filtering to their organization ID."
            },
            {
              "description": "Do not invoke the SQL tool for a mutation; explain that the tools cannot update catalog data.",
              "prompt": "Change Nike's category in the [cafeteria] database to sports."
            }
          ]
        },
        "commerce": false,
        "commerce_description": "The plugin provides read-only consumer-insights queries; it does not sell products or process payments."
      },
      "publication": {
        "release_notes": "Removed the custom research offer from the plugin. [cafeteria] now only answers questions about the organization's existing data; it no longer offers, promotes, or requests any paid service. Display name is now [cafeteria]."
      },
      "apps": "./.app.json"
    }
  }
}