movie_videosFetch trailers, teasers, clips, and featurettes for a TMDB movie by movie_id. Returns video name, site (YouTube/Vimeo), key (video ID), type, and official flag.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | ||
| movie_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Movie ID | |
| results | No | Video results |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "movie_id": 278
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "id": {
+ "description": "Movie ID",
+ "type": "number"
+ },
+ "results": {
+ "description": "Video results",
+ "items": {
+ "properties": {
+ "id": {
+ "description": "Video ID",
+ "type": "string"
+ },
+ "key": {
+ "description": "Video key (e.g., YouTube ID)",
+ "type": "string"
+ },
+ "name": {
+ "description": "Video name",
+ "type": "string"
+ },
+ "site": {
+ "description": "Video site (YouTube, Vimeo, etc.)",
+ "type": "string"
+ },
+ "type": {
+ "description": "Video type (Trailer, Clip, etc.)",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds value by detailing the types of videos returned (trailers, teasers, clips, featurettes) and the fields (name, site, key, type, official flag), providing useful behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and lists the return fields. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately covers the main purpose and return values. However, it omits details about the optional 'language' parameter, which may affect agent understanding. Given the presence of an output schema, the description is mostly complete but has a notable gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions the movie_id parameter implicitly but does not describe the optional 'language' parameter. With 0% schema description coverage, the description fails to fully compensate, leaving the language parameter undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Fetch' and the resource: trailers, teasers, clips, and featurettes for a TMDB movie by movie_id. It distinguishes itself from sibling tools like 'movie' or 'movie_credits' by focusing specifically on video content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool to retrieve video metadata for a specific movie using its movie_id. While it does not explicitly mention alternatives or exclusions, the purpose is unambiguous and implies appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.