video-understanding-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
The two tools have completely distinct purposes: video_probe inspects metadata, while video_transcribe performs audio transcription. There is no overlap or ambiguity between them.
Naming Consistency5/5Both tool names follow the same verb_noun snake_case pattern (video_probe, video_transcribe), with the action first and the domain prefix consistent. The naming is uniform and predictable.
Tool Count3/5With only two tools, the server feels thin for the broad domain of video understanding. The count is borderline but not extreme, as both operations are relevant and non-trivial.
Completeness2/5The tool surface is severely incomplete for a server named 'video-understanding'. It only covers two basic operations: metadata inspection and speech transcription. There are no tools for common video-understanding tasks such as scene detection, object recognition, action classification, or even audio extraction.
Average 4/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must stand alone. It does convey a read-only inspection via ffprobe, but it does not explicitly state that the file is unmodified, require specific permissions, or warn about failure modes. It is minimally transparent but not rich.
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?
Two sentences, each earning its place: the first defines the operation, the second clarifies the precondition. The wording is direct, efficiently front-loaded, and contains no filler.
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?
The tool has an output schema, so the return value is already documented. With only one parameter and clear purpose, the description covers the key constraint (path root). It does not address branch conditions for failure or permission, but it is sufficiently complete for a simple read-only inspection tool.
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 schema describes 'path' as an absolute path to a local media file, but the description adds an important constraint: the path must be inside an allowed read root. This goes beyond the schema and adds meaningful semantic guidance for correct invocation.
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 a specific action (inspect), resource (local media file), method (ffprobe), and output (normalised metadata). This plainly differentiates it from the sibling video_transcribe, which would perform transcription rather than metadata inspection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to choose this tool over video_transcribe. The description mentions an execution constraint (absolute path, allowed read root) but does not address selection among alternatives or any prerequisite/context beyond that.
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, the description carries the behavioral burden. It discloses that processing is offline and that the tool writes timestamped JSON and Markdown files, which conveys privacy implications and side effects. It does not detail overwrite behavior or error cases, but the key operational behavior is covered.
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?
Two concise sentences with no filler. The primary action and constraints are front-loaded, and every clause adds meaningful information.
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?
The description captures the essential context: local file input, whisper.cpp engine, offline processing, and durable outputs. An output schema exists, so return-value documentation is not required here. Minor ambiguity around 'allowed output directory' is acceptable since the schema already notes the server does not create it.
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 schema already documents all three parameters well. The description adds no parameter-level detail, but it doesn't need to because the input schema covers path, output_dir, and language 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?
States a specific verb and resource: 'Transcribe the first audio stream of a local media file with whisper.cpp.' This is clearly distinct from the sibling video_probe, which implies probing metadata rather than producing transcripts.
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 gives clear context: use this tool when you need an offline transcription of a local media file written to timestamped output files. It does not explicitly say 'use video_probe instead for metadata' or list exclusions, so it stops short of 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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