MCP FFmpeg Helper

by sworddut

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap. For example, add_watermark modifies video content, convert_video changes format, create_video_from_images builds new video, extract_audio/ extract_frames extract different media types, get_video_info provides metadata, and trim_audio/ trim_video handle trimming of different file types. The descriptions make it easy to differentiate between all tools.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as add_watermark, convert_video, extract_audio, and trim_video. This predictable naming convention makes the tool set easy to navigate and understand, with no deviations in style or structure.
Tool Count5/5
With 8 tools, this server is well-scoped for video and audio processing tasks. Each tool serves a specific, useful function in the FFmpeg domain, such as conversion, extraction, trimming, and information retrieval, without being overly sparse or bloated.
Completeness4/5
The tool set covers core FFmpeg operations like conversion, trimming, extraction, and watermarking, with good coverage for video and audio workflows. A minor gap is the lack of tools for advanced editing (e.g., merging videos, adjusting filters), but agents can likely work around this with existing tools for basic processing needs.
Average 2.9/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 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?
No annotations are provided, so the description carries full burden. 'Add a watermark to a video' implies a mutation operation that creates a new output file, but it doesn't disclose behavioral aspects like whether it overwrites existing files, requires specific permissions, handles errors, or has performance considerations. For a tool with 5 parameters and no annotations, this is a significant gap.
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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly.
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 mutation tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, how it handles errors, or the implications of creating a new video file. More context is needed given the complexity and lack of structured data.
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 description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain watermark format constraints or position defaults). Baseline 3 is appropriate when the schema does the heavy lifting.
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 action ('add a watermark') and the resource ('to a video'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'convert_video' or 'create_video_from_images', but the specific watermarking function is distinct enough to avoid confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'convert_video' that might also handle watermarks, there's no indication of prerequisites, typical use cases, or when other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 but only states the basic action. It doesn't cover critical aspects like whether the conversion is destructive to the original file, performance implications, supported formats, error handling, or rate limits. For a tool with 3 parameters and no annotations, this is a significant gap.
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 a single, efficient sentence with zero waste. It's front-loaded and directly states the tool's purpose without unnecessary elaboration, making it easy to parse quickly. This is an example of optimal conciseness for a simple tool.
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?
Given the complexity of video conversion (3 parameters, no annotations, no output schema), the description is incomplete. It lacks details on output behavior, supported formats, error cases, or how 'options' parameter interacts with conversion. For a tool that could involve format-specific nuances, this leaves too much undefined.
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?
The schema description coverage is 100%, so the input schema already documents all parameters clearly. The description adds no additional meaning beyond implying conversion between formats, which is redundant with the tool name. This meets the baseline for high schema coverage but doesn't enhance understanding.
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 purpose with a specific verb ('convert') and resource ('video file'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'create_video_from_images' or 'trim_video', which also involve video processing, so it doesn't fully distinguish its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools, prerequisites, or specific contexts for conversion, leaving the agent to infer usage based on the name alone. This lack of explicit guidance reduces its effectiveness in tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the action 'create' but lacks details on behavioral traits like whether it overwrites existing files, requires specific permissions, handles errors, or has performance implications. This is inadequate for a tool with 6 parameters and no output 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?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with no wasted content.
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?
Given the complexity of a video creation tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It lacks information on output format, error handling, dependencies, or usage context, leaving significant gaps for an AI agent.
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 description coverage is 100%, providing full documentation for all 6 parameters. The description adds no additional parameter semantics beyond the schema, so it meets the baseline of 3 without compensating or adding value.
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 verb 'create' and the resource 'video from a sequence of images', making the purpose explicit. It distinguishes from siblings like 'convert_video' or 'extract_frames' by focusing on generation from images, but doesn't explicitly mention how it differs from all siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, when not to use it, or compare to siblings like 'convert_video' or 'extract_frames' that might handle related tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 but adds minimal context. It states the action ('extract audio') but doesn't describe traits like whether it overwrites existing files, requires specific permissions, handles errors, or has performance considerations (e.g., processing time). For a mutation tool (implied by file output) with zero annotation coverage, this is a significant gap in transparency.
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 extremely concise with a single sentence that directly states the tool's purpose. It is front-loaded with no wasted words, making it easy to parse quickly. Every part of the sentence earns its place by clearly conveying the core functionality without redundancy or unnecessary elaboration.
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?
Given the tool's complexity (a mutation operation with file I/O) and the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like file handling, error conditions, or output specifics, which are crucial for safe and effective use. The high schema coverage helps with parameters, but overall context for invocation is insufficient.
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?
The description adds no parameter-specific information beyond what the schema provides. Since schema description coverage is 100%, the baseline score is 3, as the schema already documents all parameters (inputPath, outputPath, format) adequately. The description doesn't compensate with additional details like format examples or path requirements, but it doesn't need to given the high schema coverage.
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 purpose with a specific verb ('extract') and resource ('audio from a video file'), making it immediately understandable. It distinguishes from siblings like 'extract_frames' (which extracts images) and 'trim_audio' (which modifies audio), though it doesn't explicitly mention these distinctions. The purpose is unambiguous but could be more specific about sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a video file), exclusions (e.g., not for audio-only files), or comparisons to siblings like 'convert_video' (which might handle audio extraction as part of conversion) or 'trim_audio' (which modifies existing audio). Usage is implied from the purpose but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions the output format ('sequential image files') but lacks critical details: whether it overwrites existing files, requires specific permissions, handles errors, or has performance/rate limits. For a tool with 7 parameters and no annotations, this is a significant gap in transparency.
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 a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('extract frames', 'from a video', 'as sequential image files') earns its place by clarifying the tool's function, making it highly concise and well-structured.
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?
Given the complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't address behavioral aspects like file handling, error conditions, or output specifics (e.g., naming conventions, file sizes). For a tool that performs extraction with multiple options, more context is needed to guide effective use.
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?
The description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with detailed descriptions for all 7 parameters. The baseline score of 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate with additional context like default behaviors or usage examples.
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 action ('extract frames') and resource ('from a video'), specifying the output format ('as sequential image files'). It distinguishes from siblings like 'extract_audio' by focusing on visual frames rather than audio, but doesn't explicitly differentiate from other video processing tools like 'convert_video' or 'trim_video' beyond the core function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. While the description implies it's for frame extraction, it doesn't mention when to choose it over other video tools (e.g., 'get_video_info' for metadata, 'trim_video' for editing), nor does it specify prerequisites like file formats or system requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states what the tool does, not how it behaves. It doesn't disclose whether this is a read-only operation, what format the information is returned in, potential errors, or performance characteristics.
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 a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a simple tool with one parameter.
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 tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed information' includes, the return format, or error conditions. Given the lack of structured metadata, the description should provide more behavioral context.
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 description coverage is 100% with the single parameter 'filePath' well-documented in the schema. The description doesn't add any additional parameter context beyond what's already in the structured schema, meeting the baseline for high coverage.
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 verb 'Get' and resource 'detailed information about a video file', making the purpose unambiguous. However, it doesn't differentiate from potential sibling tools that might also retrieve video information with different scopes or details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'extract_frames' or 'extract_audio' which might also provide video information. The description lacks context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states the tool 'trims' audio, implying mutation, but doesn't disclose behavioral traits such as whether it modifies the original file, requires specific permissions, handles errors, or has performance constraints like file size limits. The description is minimal and lacks critical operational context.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and earns its place by clearly conveying the core functionality.
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?
Given the complexity of a mutation tool with 6 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavior, error handling, output specifics, or usage context, leaving significant gaps for an AI agent to understand how to invoke it correctly.
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 description coverage is 100%, with all parameters well-documented in the schema (e.g., paths, time formats, output format). The description adds no additional meaning beyond the schema, such as explaining parameter interactions (e.g., using 'duration' vs. 'endTime') or default behaviors. Baseline 3 is appropriate as the schema does the heavy lifting.
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 action ('trim') and resource ('audio file') with a specific purpose ('to a specific duration'). It distinguishes from siblings like 'trim_video' by specifying audio rather than video, though it doesn't explicitly contrast with 'extract_audio' which might also involve segmenting audio files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention when to choose 'trim_audio' over 'extract_audio' or other audio/video processing siblings, nor does it specify prerequisites like file formats or system requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool trims videos but doesn't mention whether this is a destructive operation, what permissions are needed, file format limitations, or error conditions. For a mutation tool with zero annotation coverage, this is inadequate.
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 a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a straightforward tool and front-loads the core functionality.
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 video editing tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, format requirements, or how it differs from similar tools. The agent would struggle to use this effectively without additional context.
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 description coverage is 100%, so the schema already documents all 5 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, but doesn't need to compensate for gaps. This meets the baseline for high schema coverage.
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 'Trim a video to a specific duration' clearly states the action (trim) and resource (video), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'trim_audio' or 'extract_frames', which would require more specificity about video-only focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'extract_frames' or 'trim_audio'. It doesn't mention prerequisites, constraints, or typical use cases, leaving the agent with minimal context for tool selection.
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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