person_combined_creditsFetch all movie and TV credits for a TMDB person by person_id. Returns cast and crew entries with title, character/job, media type, release date, and vote average.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | ||
| person_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Person ID | |
| cast | No | Cast credits | |
| crew | No | Crew credits |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "person_id": 6384
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "cast": {
+ "description": "Cast credits",
+ "items": {
+ "properties": {
+ "character": {
+ "type": "string"
+ },
+ "id": {
+ "type": "number"
+ },
+ "title": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "crew": {
+ "description": "Crew credits",
+ "items": {
+ "properties": {
+ "id": {
+ "type": "number"
+ },
+ "job": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "id": {
+ "description": "Person ID",
+ "type": "number"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context by listing specific returned fields (title, character/job, media type, release date, vote average), which is useful beyond the 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 resource, provides specifics about return data, and contains no unnecessary words.
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 tool has an output schema, so return values are covered. However, the description omits the language parameter and lacks usage guidelines, leaving minor gaps in completeness.
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 person_id in context, adding meaning. However, it does not describe the language parameter, and schema coverage is 0%, so the description only partially compensates for the missing schema descriptions.
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 it fetches all movie and TV credits for a TMDB person by person_id, naming specific return fields. This distinguishes it from sibling tools like movie_credits or person.
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 implies usage (fetching combined credits) but does not explicitly state when to use this tool over alternatives or provide any exclusions or prerequisites.
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.