TMDB MCP Server

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Get TV recommendations

get_tv_recommendations

Read-only

Fetch TV show recommendations based on co-viewing data for a given show ID. Use it to find thematically relevant shows that similar viewers also liked, with pagination support.

Instructions

Get TV shows TMDB recommends for the given show id, based on co-viewing/personalization data (what users who liked this also liked) — usually the more thematically relevant list. Prefer this over get_similar as the default choice; get_similar matches on shared genres/keywords, a blunter heuristic that can surface tonally unrelated titles. Get the id from search_tv.

Input Schema

Name	Required	Description	Default
`id`	Yes	TMDB numeric id.
`page`	No	1-based page number for pagination (TMDB returns up to 20 results per page, max 500).

Output Schema

Name	Required	Description	Default
`page`	Yes
`results`	Yes
`total_pages`	Yes
`total_results`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed11 schema fields changedv0.14.0Oct 24, 2026
- removedOutput schema / properties / results / items / properties / overview / anyOf
```
Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / results / items / properties / overview / type
```
Added value: +[
+  "string",
+  "null"
+]
```
- removedOutput schema / properties / results / items / properties / poster_url / anyOf
```
Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / results / items / properties / poster_url / type
```
Added value: +[
+  "string",
+  "null"
+]
```
- removedOutput schema / properties / results / items / properties / vote_average / anyOf
```
Removed value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / results / items / properties / vote_average / description
```
Added value: +"TMDB's own 0-10 user score. A different audience and scale from the IMDb/RT/Metacritic scores get_movie/get_tv return as `ratings` — don't compare, average or substitute across the two."
```
- addedOutput schema / properties / results / items / properties / vote_average / type
```
Added value: +[
+  "number",
+  "null"
+]
```
- removedOutput schema / properties / results / items / properties / vote_count / anyOf
```
Removed value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / results / items / properties / vote_count / type
```
Added value: +[
+  "number",
+  "null"
+]
```
- removedOutput schema / properties / results / items / properties / year / anyOf
```
Removed value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / results / items / properties / year / type
```
Added value: +[
+  "number",
+  "null"
+]
```
Addedv0.10.1Jul 30, 2026
Removedv0.8.1Jul 26, 2026
Addedv0.8.1Jul 26, 2026
Removedv0.8.0Jul 22, 2026
First observedv0.3.0Jul 9, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuine behavioral context the annotations don't: the recommendation basis is co-viewing/personalization data, which tells the agent how results are ordered and how much to trust them. Pagination and return shape are left to the schema and output schema.

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?

Three dense sentences, front-loaded with purpose, followed by the tool-selection rule and the id prerequisite. No filler; the comparative clause about get_similar earns its length by directly changing tool selection behavior.

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

Completeness5/5

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

An output schema exists, so return values need not be described, and both parameters are fully documented in the schema. Combined with the sibling routing and the id-sourcing hint, nothing an agent needs to invoke this correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents both id (TMDB numeric id) and page (pagination, max 500). The description only adds provenance for the id ("Get the id from search_tv"), which is a useful but minor supplement — baseline 3 applies.

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?

States a specific verb and resource ("Get TV shows TMDB recommends for the given show id") and immediately disambiguates from the sibling tool get_similar. The agent can distinguish this from get_similar without opening either schema.

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

Usage Guidelines5/5

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

Explicitly prescribes default choice: "Prefer this over get_similar as the default choice", then explains why the alternative differs ("matches on shared genres/keywords, a blunter heuristic that can surface tonally unrelated titles"). It also gives the prerequisite for the id parameter ("Get the id from search_tv").

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