Morpha

list_collection

List the user's reusable Collection — layers they added with add_to_collection (lower-thirds, logo stings, brand intros, or any single layer). Returns { items: [{ scope, workspaceId, sourceProjectId, sourceProjectName, ownerEmail, elementId, name, kind, childCount }] }. scope is "personal" (from the user's own solo projects) or "team" (from a workspace they belong to). Show the user each item's name (and its sourceProjectName); sourceProjectId + elementId feed add_from_collection to drop a self-contained COPY into another project. Works on a solo account (personal items always included); takes no arguments.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations, the description carries the full burden, and it delivers: it discloses the exact return shape, explains the scope field semantics, covers the solo-account edge case, and states that no arguments are required. This is far richer than a typical list-tool description.

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 dense but well organized: purpose, return format, field semantics, downstream usage, and edge case. Every sentence contributes information an agent needs, with no filler.

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 there are no parameters and no output schema, the description supplies everything needed: the response structure, the meaning of each important field, and the connection to add_from_collection. Nothing essential is missing.

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

Parameters5/5

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

The input schema has zero parameters and 100% coverage, and the description explicitly confirms 'takes no arguments.' There is no ambiguity left for an agent about what to pass.

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 action ('List') and resource ('the user's reusable Collection'), and immediately defines what that collection contains with concrete examples. It also references add_to_collection, making the tool's role among its siblings clear.

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?

Clearly describes what the tool returns and how the returned sourceProjectId and elementId feed into add_from_collection, giving an agent strong context for when to call it. It does not explicitly name alternatives or call out when not to use it, but the usage context is unambiguous.

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

A3.6/5.0

Disambiguation3/5

The tool set has several clusters that overlap conceptually: add_keyframe/add_keyframes/set_keyframes_batch, move_band/move_layer/shift_group/set_group_window, and fade_layer/set_layer_transition/set_layer_visible all target similar actions. However, each tool's description is distinct and detailed enough for an agent to disambiguate after careful reading. The sheer volume of 95 tools still creates meaningful selection risk.

Naming Consistency4/5

Tool names overwhelmingly follow a verb_noun snake_case pattern (add_, remove_, set_, list_, rename_, create_, delete_), which is predictable and readable. Minor inconsistencies exist: plural variants like add_keyframes vs add_keyframe, mixed specificity like remove_keyframe vs remove_color_keyframe, and a few oddballs like reid_project and clip_processing_status. Overall the pattern is strong and helps navigation.

Tool Count2/5

95 tools is far beyond the well-scoped range and will overwhelm agents; even a comprehensive video editor could consolidate keyframe batch operations, overlay/track manipulations, and page/group window controls. Many tools are highly specific (reid_project, safe_zones, move_band) and place burden on the agent to pick among near-synonym verbs. While the broad domain justifies many operations, this count is excessive for a coherent tool surface.

Completeness3/5

The surface covers a broad editing lifecycle: layers, keyframes, text, captions, audio, pages, groups, versions, projects, workspaces, and collections, including batch operations. However, there is no MCP tool to render/export the final MP4 (explicitly delegated to an SDK) and no upload_video tool for bringing in a clip file, leaving major end-to-end gaps. For the stated purpose of building and editing videos, these are significant omissions that force agents to stop short of delivery.

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