Skip to main content
Glama

Clipform

by io.github.Clipform

Upload Media Asset

clipform_upload_media_asset

Put one or more media files into your workspace media library (max 10, uploaded sequentially). This is step one of attaching media to a node - follow up with clipform_attach_node_media to place the returned media_asset_id on a node.

When a public URL is provided, the media is fetched and stored automatically. For video: ingested via Mux. For image: stored in Supabase. Captions from clipform_generate_tts enable per-word highlighting in the viewer once attached.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesOne or more media items to create as workspace library assets
contextYesDescribe the user's underlying goal in one sentence - not the tool you're calling.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesOne result per item, in order

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations, it discloses meaningful runtime behavior: sequential upload, server-side fetching for public URLs, Mux ingestion for video, Supabase storage for images, and caption-dependent viewer highlighting. These details materially help an agent predict side effects and prerequisites.

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 organized with the core action first, then the workflow relationship, then storage/behavior specifics. Every sentence adds operational value with no filler or repetition of names or titles.

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?

With a rich output schema implied and annotations covering mutation/idempotency, the description supplies the missing procedural context: max-10 sequential behavior, follow-up tool, storage backend, and caption integration. An agent has enough to invoke and sequence this tool correctly.

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 already covers 100% of parameter descriptions, so baseline is 3. The description adds workflow-level meaning by explaining that the returned media_asset_id feeds clipform_attach_node_media and clarifying that captions must include word arrays for highlighting, going beyond the schema.

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 specific verb and resource: 'Put one or more media files into your workspace media library' with a clear max-10 constraint. It further differentiates itself by naming the follow-up tool clipform_attach_node_media, so an agent can distinguish this upload step from the broader media workflow.

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 positions the tool as 'step one of attaching media to a node' and directs the agent to clipform_attach_node_media next. It also references clipform_generate_tts for captions, giving clear workflow context for when this tool fits versus siblings.

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

All Clipform toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation3/5

Most form/node CRUD tools are clearly distinct, but the render/generate trio (generate_video, render_video_template, render_composition) and get_responses vs get_results can be confused by name alone. The descriptions include strong disambiguation guidance, so the overlap is manageable but still present.

Naming Consistency4/5

The vast majority of tools follow a consistent clipform_verb_noun snake_case pattern, with create/get/update/delete/list used predictably. Minor deviations include get_more_tools lacking the clipform_ prefix and whoami not matching the verb_noun convention.

Tool Count2/5

At 34 tools, this is above the range where a toolset feels well-scoped, and several entries are auxiliary or internal (whoami, log_generation, get_more_tools, search_news). The domain is broad, but the surface could be consolidated without losing core capabilities.

Completeness4/5

The set covers form and node lifecycle, media upload/attachment, logic wiring, publishing, responses/results, and content generation (TTS, video, music, stock media). Minor gaps remain, such as no conditional branching in set_logic and no general media-library listing tool.

Resources