freedom-mcp

generate_video

Generate a video clip for the company (xAI Imagine Video 1.5, 3 credits): text-to-video, image-to-video, multi-image reference (up to 7), or video edit with native audio. Use when an operator or agent needs social, product, narrated, or brand video up to 15s / 1080p. This is the only video generation door.

[sensitive-tier, initiates a multi-step agent process — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

Input Schema

TableJSON Schema

Name	Required	Description
`prompt`	Yes	Detailed description of the video to generate. Include visual scene, audio/voice direction, mood, and brand elements. For multi-image: describe how the subjects from each image interact. For video editing: describe the changes to make.
`duration`	No	Video duration in seconds (1–15, primitive max). Use the length the shot needs — not an FO soft cap. Default 5 only when omitted. Not supported for video editing.
`companyId`	Yes	FreedomOS company id to act within (you must be a member). Required for company-scoped tools.
`image_url`	No	URL of a single still image to animate (image-to-video mode). Use image_url from a previous generate_image result. For multiple images, use image_urls instead.
`video_url`	No	URL of an existing video to edit (video editing mode). Describe the edits in the prompt. Input capped at 8.7 seconds (primitive).
`image_urls`	No	Array of image URLs (up to 7, primitive max) for reference-to-video. Combine mascot, person, product, brand assets. Use signed URLs from MEDIA IN THIS CONVERSATION. For a single image, use image_url instead.
`resolution`	No	Video resolution. 480p (fast draft), 720p (HD), 1080p (full HD on text-to-video and image-to-video). Reference-to-video is automatically clamped to 720p (primitive). Not supported for video editing.
`artifact_id`	No	ID of a single existing artifact from the MEDIA IN THIS CONVERSATION block. The system resolves a fresh signed URL and auto-detects: image artifacts → image-to-video, video artifacts → video editing. For multiple images, use artifact_ids instead.
`artifact_ids`	No	Array of artifact IDs (up to 7, primitive max) for reference-to-video. System resolves fresh signed URLs for each.
`aspect_ratio`	No	Aspect ratio. Default: 16:9. For image-to-video, defaults to the input image ratio. Not supported for video editing.
`save_to_drive`	No	If true, also save the video to Google Drive. Defaults to false.

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 of behavioral disclosure. It adds valuable context about the sensitive-tier nature, multi-step approval process, and credit cost (3 credits). However, it omits details like error handling, rate limits, or what happens on credit exhaustion, so it is not fully transparent.

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 two sentences plus a bracketed note, all front-loaded with the core purpose. Every sentence adds unique information with no redundancy or filler. It is a model of conciseness.

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 11 parameters and no output schema. The description covers the main modes, limitations (15s, 1080p), and approval process, but does not describe the return value (e.g., video URL, artifact ID) or error behavior. Given the complexity, it is adequate but has clear gaps.

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 has 100% coverage with detailed parameter descriptions. Beyond that, the description adds context about the different generation modes, the model (xAI Imagine Video 1.5), and the approval flow, which helps the agent understand parameter selection in context. This extra value raises the score above the baseline 3.

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 the tool generates a video clip, lists the four modes (text-to-video, image-to-video, multi-image reference, video edit), and explicitly declares it is 'the only video generation door,' distinguishing it from image generation siblings like generate_image_xai.

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 specifies when to use the tool: 'when an operator or agent needs social, product, narrated, or brand video up to 15s / 1080p.' It also states it is the sole video generation tool, but does not provide explicit exclusions or alternatives (e.g., for longer videos), keeping it from a 5.

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

Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

Resources

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