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Glama

Tmdb

by io.github.pipeworx-io

Movie Recommendations

movie_recommendations
Read-onlyIdempotent

Fetch TMDB-recommended movies similar to a given movie by movie_id. Returns title, overview, release date, popularity, vote average, and poster path for each recommended film.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
languageNo
movie_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoCurrent page number
resultsNoRecommended movies
total_pagesNoTotal pages available
total_resultsNoTotal results

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "movie_id": 550
+  },
+  {
+    "movie_id": 278,
+    "page": 1
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "page": {
+      "description": "Current page number",
+      "type": "number"
+    },
+    "results": {
+      "description": "Recommended movies",
+      "items": {
+        "properties": {
+          "id": {
+            "description": "Movie ID",
+            "type": "number"
+          },
+          "title": {
+            "description": "Movie title",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total_pages": {
+      "description": "Total pages available",
+      "type": "number"
+    },
+    "total_results": {
+      "description": "Total results",
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, non-destructive. Description adds source (TMDB) and output fields, but doesn't disclose rate limits or pagination details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no fluff, clear and direct.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Output schema exists, so return values are covered. However, description omits pagination and language parameter explanations, and lacks usage boundaries.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 3 params with 0% coverage. Description only implicitly mentions movie_id, but does not explain page or language parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states fetching TMDB recommended movies similar to a given movie by movie_id, listing returned fields. Distinct from siblings like search_movie or movie.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies use when you have a movie_id and want similar movies, but no explicit when-not or alternatives provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation2/5

The tool set blends two unrelated domains (TMDB and Pipeworx). Among Pipeworx tools, several overlap heavily (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, suggest_questions) with vague boundaries, making it hard for an agent to pick the right one. TMDB tools are distinct but the overall mixture creates confusion about which domain a request belongs to.

Naming Consistency3/5

All tools use snake_case, which is consistent. However, naming styles vary widely: TMDB tools use simple noun or verb-first names (movie, search_movie, discover_tv), while Pipeworx tools use longer descriptive phrases with prefixes (ask_pipeworx, polymarket_arbitrage, entity_profile). The pattern is not predictable across the set.

Tool Count2/5

50 tools is excessive for a server named 'Tmdb'. Only about 18 tools are actually TMDB-related; the remaining 32 belong to the Pipeworx ecosystem. This inflates the count and makes the server feel bloated and unfocused, far beyond a well-scoped TMDB server.

Completeness3/5

The TMDB portion is quite complete (search, discover, details, credits, recommendations, trending, genres, configuration). However, the server's overall scope is muddled—it tries to cover two disjoint domains, so no single domain feels fully fleshed out. There are also some missing TMDB features (e.g., upcoming/now playing) that would require extra discovery. The Pipeworx tools cover data broadly but overlap in coverage.

Resources