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Complete Media Upload

clipform_complete_media_upload
Idempotent

Confirm a signed-PUT still image upload finished, after PUTting the bytes to the upload_url returned by clipform_upload_media_asset. The API verifies the object actually landed in storage before flipping the asset from processing to ready - call this right after the PUT succeeds, or the asset stays invisible in the library. Not needed for video uploads (TUS/Mux settle automatically).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesDescribe the user's underlying goal in one sentence - not the tool you're calling.
media_asset_idYesThe media_asset_id returned by clipform_upload_media_asset for the still image

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesThe asset's status after this call - ready on success, or its already-settled status when called again (noop)
media_asset_idYes

Schema Changelog

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

  1. Changed3 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / context
      Added value: +{
      +  "description": "Describe the user's underlying goal in one sentence - not the tool you're calling.",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "media_asset_id"
      -]New value: +[
      +  "media_asset_id",
      +  "context"
      +]
  2. Added

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (idempotentHint, readOnlyHint false), the description reveals meaningful behavior: the API verifies storage before flipping status, and this call is required for visibility. It also notes that video uploads are handled automatically, adding real behavioral context not present in annotations or 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?

Three sentences, all necessary: action, mechanism/timing, and exclusion. The most important instruction is front-loaded, and there is no filler 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?

The description fully explains the tool's role in the upload workflow, including prerequisites, timing, consequences of misuse, and when it is unnecessary. With an output schema available and strong annotations, nothing an agent needs to correctly invoke this tool is missing.

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 coverage is 100%, so the baseline is 3. The description reinforces that media_asset_id comes from clipform_upload_media_asset but doesn't add new parameter semantics beyond what the schema descriptions already provide.

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 states the exact action ('Confirm a signed-PUT still image upload finished') and ties it to a specific resource and prior step (upload_url from clipform_upload_media_asset). It clearly differentiates from the upload tool and clarifies scope (still images only).

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 tells the agent when to call ('right after the PUT succeeds') and what happens if it doesn't ('asset stays invisible in the library'). It also gives a clear exclusion for video uploads, so the agent knows when not to use it.

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

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: form CRUD, node management, media upload/attach, rendering, search, and guidance retrieval are all separable. The main overlap is among the three render tools (clipform_generate_video, clipform_render_video_template, clipform_render_composition), but their descriptions include explicit disambiguation guidance, so an agent can correctly choose. clipform_get_guide and clipform_get_workflow are also similar but clearly differentiated.

Naming Consistency4/5

Tool names follow a consistent clipform_<verb>_<noun> pattern throughout, e.g., clipform_create_form, clipform_add_node, clipform_update_node, clipform_delete_node. Minor deviations exist: clipform_whoami is not verb_noun, and get_more_tools lacks the clipform_ prefix, but these are edge cases and the overall convention is highly predictable.

Tool Count3/5

34 tools is on the heavy side for a single MCP server. The server covers a broad domain (form creation, node editing, media management, video rendering, TTS, search, guidance, imports, responses), so the count is defensible, but it is above the typical well-scoped range and may add navigation overhead.

Completeness5/5

The tool surface covers the full lifecycle: create/read/update/delete forms and nodes, media upload/attach/delete, multiple render paths with status checking, TTS generation, music/image/video search, form import, response retrieval, and workflow/guide knowledge. The main gap is lack of a direct branching-logic editor (option-based branching is only in the dashboard), but the API consciously documents that limitation and the rest of the lifecycle is complete.