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Pictory Integrations

pictory_integrations

Manage cloud integrations for Pictory: connect Vimeo or AWS S3, check quotas and AI credits, and clean stuck render jobs.

Instructions

Manage third-party cloud integrations (Vimeo & AWS S3), account quotas, AI credits, and job cleanup.

Supported Actions:

  • 'get_quota': Check current API video render quota and usage limits (GET /v1/quota).

  • 'get_credit_usage': Check remaining AI generation credits and breakdown (GET /v1/aicredits/usage).

  • 'list_jobs': List recent and running render jobs across your account (GET /v1/jobs).

  • 'clean_job': Cancel or delete a stuck/failed job (DELETE /v1/jobs/{job_id}/clean).

  • 'list_vimeo_connections': List connected Vimeo accounts for direct video publishing (GET /v1/vimeo-connections).

  • 'get_vimeo_connection': Get details for a Vimeo connection (GET /v1/vimeo-connections/{id}).

  • 'create_vimeo_connection': Authorize a new Vimeo connection (POST /v1/vimeo-connections).

  • 'update_vimeo_connection': Update an existing Vimeo connection (PUT /v1/vimeo-connections/{id}).

  • 'delete_vimeo_connection': Disconnect a Vimeo account (DELETE /v1/vimeo-connections/{id}).

  • 'list_aws_connections': List private AWS S3 bucket connections (GET /v1/awsconnections).

  • 'get_aws_connection': Get details for an AWS private S3 connection (GET /v1/awsconnections/{id}).

  • 'create_aws_connection': Connect a private AWS S3 bucket using IAM keys (POST /v1/awsconnections).

  • 'update_aws_connection': Update an AWS private S3 connection (PUT /v1/awsconnections/{id}).

  • 'delete_aws_connection': Remove an AWS connection (DELETE /v1/awsconnections/{id}).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
actionYes
job_idNo
page_sizeNo
connection_idNo
connection_payloadNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses state-changing behavior through action verbs like 'Cancel', 'Delete', 'Disconnect', 'Authorize', 'Connect', and 'Remove', and labels clean_job as affecting 'stuck/failed' jobs. However, it does not disclose consequences, reversibility, permissions, or side effects beyond the surface action, so transparency is partial.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description starts with a one-sentence overview and then uses a clean bullet list where each action has an inline command snippet and a short gloss. It is long, but the length is warranted by the 14 actions. No wordy filler is present, though a legend for parameter usage would be more efficient than repeated endpoint notation.

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

Completeness2/5

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

For a complex multi-action dispatcher with 6 parameters and no annotation coverage, the description is incomplete. It fails to specify which parameters are required for each action, what connection_payload should contain, the valid values for action, or how list actions use pagination. The output schema's existence doesn't compensate for missing operation-to-parameter mapping, so an agent cannot reliably construct valid requests.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It lists action names and endpoints including {id} placeholders, implying job_id and connection_id usage, but it never explicitly maps schema fields (action, page, page_size, connection_payload, job_id, connection_id) to actions. The connection_payload parameter is not mentioned at all, and page/page_size are undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's domain ('Manage third-party cloud integrations, account quotas, AI credits, and job cleanup') and enumerates 14 specific actions with endpoints and one-line behaviors. It distinguishes itself from siblings like pictory_video and pictory_transcribe through its focus on integrations, quotas, credits, and jobs. The verb 'Manage' is broad, but the action list provides concrete specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied through each action's description (e.g., 'Cancel or delete a stuck/failed job' tells when clean_job is appropriate), but there is no explicit guidance on when to use this tool vs. sibling tools like pictory_video or pictory_projects. No exclusions or alternatives are named, leaving tool selection to inference from the action list.

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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