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search_film_mcps

Search the mcp.film directory of MCP servers for AI filmmaking. Filter by free-text query (matches name, vendor, tagline, capabilities), category id, or capability. Returns compact entries; use get_film_mcp for full detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoFree-text search, e.g. 'upscale video' or 'voice cloning'
categoryNoCategory id (see list_film_categories)
capabilityNoExact capability tag, e.g. 'image-to-video'
remote_onlyNoOnly hosted remote MCPs (no local install)
official_onlyNoOnly vendor-maintained servers

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that results are compact, that free-text matches name, vendor, tagline, and capabilities, and that full detail is available via get_film_mcp. It notably adds context beyond the schema, but does not mention pagination, sort order, or filter combination behavior.

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 extremely efficient, consisting of two sentences that front-load the primary action ('Search the mcp.film directory'), then list filters and the key distinction from get_film_mcp. Every phrase serves a purpose, with no redundancy or filler.

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

Completeness3/5

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

The tool has 5 parameters and no output schema, so the description should clarify how filters interact and what fields the compact entries contain. The use of 'or' is ambiguous—it could imply filters are mutually exclusive—and the result structure is not described. These gaps are notable given the absence of an output schema.

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?

The schema covers 100% of parameters, giving a baseline of 3. The description enriches this by explaining that free-text query matches name, vendor, tagline, and capabilities—information not present in the schema. It also reinforces the category and capability filters, adding meaningful semantic context.

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 clearly states it searches the mcp.film directory of MCP servers for AI filmmaking, with specific mention of filters and the compact nature of results. It also distinguishes itself from sibling tool get_film_mcp by explicitly directing users there for full detail, leaving no ambiguity about its scope.

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 provides clear context: this is the search tool for the mcp.film directory, and it explicitly names get_film_mcp as the alternative for full detail. It also references list_film_categories in the schema for category IDs, though it doesn't detail all when-not-to-use scenarios for every sibling.

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

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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target distinct entities (capabilities, playbooks, recommendations, servers, install configs). The only potential confusion is between plan_film_stack and recommend_film_mcps, but their descriptions clarify different scopes: full pipeline vs intent-routed brief.

Naming Consistency5/5

All tools follow a consistent verb-first snake_case pattern: get_ for singular resources, list_ for plural, plus search_, plan_, recommend_, and submit_. No mixed conventions or vague verbs.

Tool Count5/5

15 tools is at the upper end of the ideal range but each earns its place: search, retrieval, listing, planning, recommendation, install config, and submission. No redundant tools.

Completeness4/5

Covers the full directory lifecycle: discovery, retrieval, contextual listings, planning, recommendations, install config generation, and submission. Minor gap: there's no explicit list-all-servers endpoint, but search_film_mcps can fulfill that role.