Skip to main content
Glama
iamneilroberts

imdb-analytics-mcp

Find Collaborations

find_collaborations
Read-onlyIdempotent

Find who has worked with whom using five collaboration modes, from an actor's frequent partners to shared titles, pairwise matches, and degrees of separation.

Instructions

Who has worked with whom, in five shapes selected by mode.

Answers questions like: "Which actors have worked with Samuel L. Jackson most often?" (collaborators_of, one id), "What films do Jackson and Walken share?" (shared_titles, two ids), "Which two people in this list have appeared together most?" (pairwise, two or more ids), "Who has worked with all five of these people?" (worked_with_all, one or more ids), "How many steps connect these two?" (degrees_of_separation, two ids, at most three hops).

Every mode counts at the unit level, so a series shared across forty episodes counts once, and every mode honours the credit definition, so "only their films together" is include_tv_series=false, include_tv_movies=false, include_video=false. limit bounds the returned collaborators; max_hops bounds the path search.

The hard limit is the data, not the query: IMDb's principal-cast list holds at most 69 people per title, so a shared credit means both people are in that top-billed subset. Its absence is not evidence they never worked together, and a "no path found" result means no path through principal casts within the hop limit. Pass ids, not names; use search_people first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
limitNo
max_hopsNo
person_idsNo
credit_definitionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses counting semantics (series counted once per unit), credit-definition honoring, the principal-cast hard limit of 69 people per title, and the crucial caveat that absence of a shared credit is not evidence against collaboration. This is exceptionally useful behavioral context.

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 long, but every sentence carries useful information for a multi-mode tool. It is front-loaded with the core question, then organizes mode behavior, shared semantics, and data caveats in clear paragraphs. There is no fluff or repetition.

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?

Given the tool's complexity, the description covers the five distinct modes, the role of key parameters, the data limitations, and the necessary search_people prerequisite. An output schema exists, so the description does not need to explain return values. This is a complete and self-sufficient definition.

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

Parameters4/5

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

Although the top-level schema has little description coverage, the prose explains the mode enum with five worked examples, states that limit bounds returned collaborators, and that max_hops bounds the path search. It also conveys the meaning of credit_definition through the include_tv_series/include_tv_movies/include_video example. It does not formally name the person_ids parameter, but the examples and 'Pass ids, not names' adequately compensate.

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?

The description opens with a clear query intent, 'Who has worked with whom,' and then enumerates all five modes with concrete example questions. It also distinguishes itself from sibling tools by instructing the agent to 'use search_people first' for name resolution, making its role unambiguous.

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?

The description gives strong usage context: which mode to pick for which question shape, the meaning of limit and max_hops, and the prerequisite 'Pass ids, not names; use search_people first.' It does not explicitly contrast with siblings like compare_people or rank_people, but the mode examples make the intended use clear.

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