Grok Imagine Video MCP Server
Server Quality Checklist
Latest release: v1.8.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: generate creates new videos, edit modifies existing ones, extend continues them, and upload_file handles file ingestion. No overlap or ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case (generate_video, edit_video, extend_video, upload_file). The pattern is uniform and predictable.
Tool Count5/5With 4 tools, the server is well-scoped for video generation. Each tool serves a necessary core function without redundancy or bloat.
Completeness5/5The tool set covers the full video lifecycle: generate, edit, extend, and upload. There are no obvious missing operations for the stated domain.
Average 4.2/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It explains the core action and duration range but omits details like authentication, rate limits, side effects (e.g., file uploads for video_path), and failure modes. The model compatibility caveat is only in the schema, not the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose, and contains no filler. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic workflow but does not mention the three mutually exclusive source options (video_url, video_path, video_file_id) or the output_path. It also omits that model grok-imagine-video-1.5 does not support extension. While the schema fills many gaps, the description alone would leave users uncertain about the full input flexibility.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description needs to add limited extra meaning. It mentions source URL and prompt, but the schema already describes each parameter fully. The 'default 6' is also already in the schema, so the description adds no novel semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extend') and resource ('an existing video'), clearly distinguishing it from siblings like generate_video and edit_video. It also names the underlying API, adding specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context: use for extending an existing video with a prompt. It does not explicitly contrast with generate_video or edit_video, but the context is unambiguous. No exclusions are stated, so not a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the 8.7-second maximum length and the fact that the edited video has the same duration as the original, which are useful behavioral details. However, it omits the model parameter caveat (grok-imagine-video-1.5 does not support editing) and does not describe error handling or processing behavior, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, each adding value: it states the purpose, gives a usage instruction, and lists key constraints. It is front-loaded with the core action and contains no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 6 parameters, no annotations, and no output schema, the description covers the essential behavior (editing existing video), key constraints (8.7s max, same duration), and offers a usage hint. However, it does not mention the model caveat or the exclusive-or relationship between video_url, video_path, and video_file_id, though these are present in the schema. It is fairly complete but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add much beyond the schema; it mentions providing a 'source video URL along with a prompt,' but the schema already documents all parameters and their constraints, including the mutually exclusive video source fields and the 8.7-second limit. The description adds no new parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the function: 'Edit an existing video' using the xAI Grok Imagine Video API. It also specifies key constraints (max 8.7 seconds, same output duration) that distinguish it from sibling tools like generate_video and extend_video, which create or extend videos rather than edit them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description establishes a clear context: it is for editing an existing video. This implicitly differentiates it from siblings that generate, extend, or upload videos. However, it does not explicitly state when not to use this tool or name alternative tools, so it lacks explicit exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so thoroughly. It discloses that the output MP4 always includes an auto-generated audio track with no audio parameter, explains resolution restrictions (1080p only with certain model), mentions automatic file upload for large image_path, and clarifies incompatibilities between input methods. This is substantial behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph but every sentence contributes necessary details (modes, aspect ratios, duration, resolution, audio behavior, input requirements). It is front-loaded with the primary purpose. While it could be broken into bullets, the length is justified given the tool's complexity, and there is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 parameters and no output schema, the description covers most behavioral aspects: modes, constraints, and input options. The main gap is that it does not explicitly state the return value or side effects (e.g., returns the output file path, uploads to Files API). Despite this, it provides enough context for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, giving a baseline of 3. The description adds value by clarifying parameter interdependencies (e.g., prompt required for T2V/R2V, optional for I2V), model-specific restrictions (1080p, R2V availability), and the behavior of image_path (base64 upload path). This enriches the schema without being redundant.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Generate a new video using xAI Grok Imagine Video API,' which clearly states the action (generate) and resource (new video), and distinguishes this from sibling tools like edit_video and extend_video since it creates a new video. It further lists supported modes (T2V, I2V, R2V), providing a precise scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use each mode (e.g., 'For image-to-video, provide image_url, image_path, or image_file_id') and states model-specific constraints, but it does not explicitly compare against sibling tools or provide 'when not to use' guidance. The context is clear and actionable, but lacks explicit exclusions or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses that the file stays private, returns a file_id, and supports specific formats/size limits. While it doesn't discuss persistence or side effects, the information provided is sufficient for safe use of a basic upload operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: the first sentence gives the core purpose, followed by useful context on privacy, reuse, and constraints. Every sentence adds necessary information with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single parameter, no output schema, and no annotations, the description fully covers purpose, return value, privacy, supported formats, size limit, and downstream usage. It is complete and self-sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers file_path with a clear description (100% coverage). The description adds value by specifying allowed file types and the 48 MB limit, which gives the agent practical constraints beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Upload a local image or video file'), the target resource ('xAI Files API'), and the primary output ('get a file_id'). It also distinguishes itself from sibling tools (generate_video, edit_video, extend_video) by positioning the file_id as reusable input for those tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use it ('reusing the same asset across multiple calls without re-uploading') and specifies constraints (supported formats, max size). It does not explicitly state when not to use it or mention alternative methods, but the context is clear enough for a simple upload tool.
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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