TMDB MCP Server

Similar TV Shows

tv_similar

Find TV shows similar to a specific series using its TMDB ID. This tool helps discover related content based on the selected show's characteristics.

Instructions

Get similar TV shows by ID

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tv_id": "<tv_id>"
    },
    "name": "tv_similar"
  }
}

Input Schema

Name	Required	Description	Default
`tv_id`	Yes	TMDB TV show ID
`page`	No	Page number (1-1000)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Apr 21, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions nothing about behavioral traits: no information on rate limits, authentication needs, pagination behavior (despite a 'page' parameter), what 'similar' means algorithmically, or the response format. This is inadequate for a tool with parameters and no 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?

The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without fluff. It's appropriately sized for a simple lookup tool.

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

Completeness2/5

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

Given no annotations, no output schema, and a parameterized tool, the description is incomplete. It lacks crucial context: what 'similar' entails, pagination details, response structure, or error handling. This leaves significant gaps for an agent to use the tool effectively.

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%, with clear parameter descriptions in the schema. The description adds no additional meaning beyond implying 'tv_id' is used to find similar shows and 'page' is for pagination, which is already covered. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the verb ('Get') and resource ('similar TV shows'), specifying it operates 'by ID'. It distinguishes from siblings like 'tv_details' (which gets details) and 'tv_popular' (which gets popular shows), but doesn't explicitly contrast with 'movie_similar' (which does the same for movies) or explain why to use this over other recommendation tools.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'movie_similar' (for movies), 'tv_recommendations' (if available as a sibling, though not listed), or other TV show discovery tools (e.g., 'tv_popular'). It only states what it does, not when it's appropriate.

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