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bitscorp-mcp

MCP FFmpeg Video Processor

by bitscorp-mcp

MCP FFmpeg 비디오 프로세서

대장간 배지

FFmpeg를 사용하여 비디오 파일을 조작하는 Node.js 서버입니다. 이 서버는 다음과 같은 API를 제공합니다.

  • 비디오 크기를 다양한 해상도(360p, 480p, 720p, 1080p)로 조절하세요

  • 다양한 포맷(MP3, AAC, WAV, OGG)의 비디오에서 오디오 추출

필수 조건

이 애플리케이션을 실행하기 전에 다음이 설치되어 있어야 합니다.

  1. Node.js (v14 이상)

  2. FFmpeg - 비디오 처리에 필요합니다.

FFmpeg 설치

macOS에서:

지엑스피1

Ubuntu/Debian의 경우:

sudo apt update
sudo apt install ffmpeg

Windows의 경우:

  1. 공식 웹사이트 에서 FFmpeg를 다운로드하세요

  2. 파일을 폴더(예: C:\ffmpeg )에 추출합니다.

  3. PATH 환경 변수에 bin 폴더를 추가합니다.

Related MCP server: ffmpeg-mcp

설치

  1. 이 저장소를 복제하세요:

git clone https://github.com/bitscorp-mcp/mcp-ffmpeg.git
cd mcp-ffmpeg
  1. 종속성 설치:

npm install

Smithery를 통해 설치

Smithery를 통해 Claude Desktop용 mcp-ffmpeg를 자동으로 설치하려면:

npx -y @smithery/cli install @bitscorp-mcp/mcp-ffmpeg --client claude

서버 실행

다음을 사용하여 서버를 시작합니다.

npm start

파일 변경 시 자동 재시작 기능을 사용하여 개발하는 경우:

npm run dev

Smithery를 통해 설치

Smithery를 통해 Claude Desktop용 mcp-ffmpeg를 자동으로 설치하려면:

npx -y @smithery/cli install @bitscorp-mcp/mcp-ffmpeg --client claude

커서용 mcp-ffmpeg를 설치하려면 설정 -> 커서 설정 -> 기능 -> MCP 서버 -> + 추가로 이동하세요.

유형 선택: 명령을 선택하고 Adjust의 API 키를 사용하여 아래를 붙여넣습니다.

npx -y @smithery/cli@latest run @bitscorp/mcp-ffmpeg

Claude Desktop과 함께 사용

이 MCP FFmpeg 서버는 Claude Desktop과 통합되어 자연어 요청을 통해 비디오를 처리할 수 있습니다.

npx로 실행

npx를 사용하여 서버를 직접 실행할 수 있습니다.

npx /path/to/mcp-ffmpeg

또는 npm에 패키지를 게시한 경우:

npx mcp-ffmpeg

Claude Desktop 구성

이 서버를 Claude Desktop에 추가하려면 Claude Desktop 구성 파일을 업데이트하세요.

  1. Claude Desktop 구성 파일을 찾으세요.

    • macOS: ~/.config/claude-desktop/config.json 또는 ~/Library/Application Support/Claude Desktop/config.json

    • Windows: %APPDATA%\Claude Desktop\config.json

    • 리눅스: ~/.config/claude-desktop/config.json

  2. mcpServers 섹션에 FFmpeg MCP 서버를 추가합니다.

{
    "mcpServers": {
        "ffmpeg": {
            "command": "npx",
            "args": [
                "--yes",
                "/absolute/path/to/mcp-ffmpeg"
            ]
        }
    }
}

npm에 패키지를 게시한 경우:

{
    "mcpServers": {
        "ffmpeg": {
            "command": "npx",
            "args": [
                "--yes",
                "mcp-ffmpeg"
            ]
        }
    }
}
  1. 변경 사항을 적용하려면 Claude Desktop을 다시 시작하세요.

클로드에 대한 예시 프롬프트

구성이 완료되면 다음과 같은 프롬프트를 사용할 수 있습니다.

Using the ffmpeg MCP server, please resize the video at /path/to/video.mp4 to 720p resolution.

노트

  • 업로드된 영상은 uploads 디렉토리에 임시로 저장됩니다.

  • 처리된 비디오 및 오디오 파일은 output 디렉토리에 저장됩니다.

  • 서버는 업로드 파일 크기를 500MB로 제한합니다.

특허

MIT

Available Tools

4 tools
extract-audioC

Extract audio from a video file

ParametersJSON Schema
NameRequiredDescriptionDefault
videoPathYesPath to the video file to extract audio from
formatNoAudio format to extractmp3
outputDirNoOptional directory to save the output file (defaults to a temporary directory)

TDQS

C2.9/5.0
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 states what the tool does but doesn't cover important behavioral aspects like whether it modifies the original video file, what permissions are needed, error handling, or performance characteristics. The description is minimal and lacks 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 extremely concise with just one sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it front-loaded and efficient. Every word earns its place in 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 lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., path to extracted audio file, success/failure indicators) or important behavioral details. For a tool that performs file operations with multiple parameters, more context is needed for 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 doesn't add any parameter information beyond what's already in the schema, which has 100% coverage with clear descriptions for all parameters. The baseline score of 3 reflects that the schema adequately documents parameters, so the description doesn't need to compensate but also doesn't provide additional 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 tool's purpose with a specific verb ('extract') and resource ('audio from a video file'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-video-info' or 'resize-video', which might also involve video processing but serve different functions.

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 or any context-specific usage scenarios, leaving the agent to infer based on tool names alone. There's no explicit when/when-not or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get-ffmpeg-versionA

Get the version of FFmpeg installed on the system

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.5/5.0
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 states the tool retrieves version information, implying a read-only operation, but does not disclose potential side effects, error conditions, permissions required, or output format. This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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, clear sentence that directly states the tool's purpose without any unnecessary words or structural fluff. It is front-loaded and efficiently communicates the essential information, 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.

Completeness3/5

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate for a basic read operation but incomplete for practical use. It lacks details on output format (e.g., string, object), error handling, or system dependencies, which are important for an agent to invoke it correctly in varied contexts.

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 input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description appropriately does not mention parameters, aligning with the schema. Since there are no parameters to explain, this meets the baseline for tools without inputs, though it doesn't add extra semantic context.

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 specific action ('Get') and resource ('version of FFmpeg installed on the system'), distinguishing it from sibling tools like 'extract-audio' or 'resize-video' which perform different operations. It precisely defines what the tool does without being vague or tautological.

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 'get-video-info' (which might include version information) or other system-check tools. It lacks explicit context, prerequisites, or exclusions, offering only a basic statement of purpose without usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get-video-infoC

Get detailed information about a video file

ParametersJSON Schema
NameRequiredDescriptionDefault
videoPathYesPath to the video file to analyze

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden but only states what the tool does without behavioral details. It doesn't disclose if this is a read-only operation, potential errors (e.g., invalid paths), performance aspects, or output format, which are critical for a tool with 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 function without unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' includes (e.g., metadata, duration, resolution) or behavioral traits, leaving gaps that could hinder an agent's ability to use the tool effectively.

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%, with the single parameter 'videoPath' documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, so it meets the baseline for high coverage without extra 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 action ('Get detailed information') and resource ('about a video file'), making the tool's purpose understandable. However, it doesn't differentiate from sibling tools like 'get-ffmpeg-version' or 'resize-video' beyond the general video focus, which keeps it from a perfect score.

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. The description lacks context about prerequisites, such as needing a valid video file path, or comparisons to siblings like 'extract-audio' for audio-related tasks, leaving usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

resize-videoB

Resize a video to one or more standard resolutions

ParametersJSON Schema
NameRequiredDescriptionDefault
videoPathYesPath to the video file to resize
resolutionsYesResolutions to convert the video to
outputDirNoOptional directory to save the output files (defaults to a temporary directory)

TDQS

B3.1/5.0
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 of behavioral disclosure. It states the action ('resize a video') but doesn't describe what happens (e.g., creates new files, overwrites existing ones, requires specific permissions, or has performance/rate limits). For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.

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 with the core action ('resize a video') and adds clarifying detail ('to one or more standard resolutions'). Every part of the sentence earns its place by specifying scope and output.

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?

Given the tool's moderate complexity (a mutation operation with 3 parameters), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, error handling, or output format. For a video processing tool, more context on file formats, processing time, or result location would be beneficial.

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 three parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'standard resolutions', which aligns with the enum in the schema but doesn't provide additional context like aspect ratio preservation or quality settings. 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 verb 'resize' and resource 'video', specifying it converts to 'standard resolutions'. It distinguishes from sibling tools like 'extract-audio' or 'get-video-info' by focusing on resolution transformation rather than extraction or metadata retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., 'get-ffmpeg-version' is clearly different).

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., video file format compatibility), when not to use it (e.g., for non-standard resolutions), or how it relates to sibling tools like 'extract-audio' for audio-only processing. Usage is implied only by the tool name and description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

TDQS

B3.1/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: extract-audio handles audio extraction, get-ffmpeg-version checks system version, get-video-info provides metadata, and resize-video adjusts video dimensions. There is no overlap in functionality, making tool selection unambiguous.

Naming Consistency4/5

The tools follow a consistent verb-noun pattern with hyphens (e.g., extract-audio, resize-video), except for get-ffmpeg-version which includes an extra noun. This minor deviation does not significantly impact readability or predictability.

Tool Count3/5

With only 4 tools, the set feels thin for a video processing domain. While the tools cover basic operations, there are likely gaps for common tasks like format conversion, trimming, or adding effects, which might limit agent effectiveness.

Completeness2/5

The tool set is severely incomplete for video processing. It lacks essential operations such as format conversion, trimming/cutting, merging videos, adding subtitles, or applying filters. This will cause frequent agent failures when handling typical video editing workflows.

Maintenance

ActivityInactive
ResponsivenessSyncing

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