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FFmpeg MCP Server

FFmpeg MCP 服务器

本 README 文件提供了有关ffmpeg-mcp代码库的信息,该代码库包含一个与 FFmpeg 兼容的 MCP 服务器。下方提供了该代码库的详细信息,以及访问最新版本的链接。

🌟 关于仓库

存储库名称: ffmpeg-mcp

简短描述: FFmpeg 的 MCP 服务器

**主题:**未提供

Related MCP server: Project Content Server

🚀 开始使用

要访问 FFmpeg 的 MCP 服务器的最新版本,请点击以下链接:

下载 MCP 服务器

如果链接包含路径部分,请下载指定的文件并执行它以开始使用 MCP 服务器。

如果链接仅包含域名,只需访问提供的链接即可浏览和下载最新版本。

如果提供的链接不起作用或不是您提供的,我们建议您检查此存储库的“发布”部分以获取最新更新。

📦 功能

以下是ffmpeg-mcp存储库的一些主要功能:

  • **MCP 服务器兼容性:**专门构建以与 FFmpeg 无缝协作。

  • **增强性能:**针对媒体处理任务的效率和速度进行了优化。

  • **安全通信:**实施数据传输的安全通信协议。

  • **可扩展架构:**旨在处理大量媒体处理请求。

🛠️ 安装

要安装 FFmpeg 的 MCP 服务器,请按照以下步骤操作:

  1. 从提供的链接下载最新版本。

  2. 执行下载的文件以开始安装过程。

  3. 按照屏幕上的说明完成安装。

  4. 开始使用带有 FFmpeg 的 MCP 服务器满足您的媒体处理需求。

📜 使用

安装完成后,您可以按照以下步骤将 MCP 服务器与 FFmpeg 一起使用:

  1. 根据您的要求配置服务器设置。

  2. 将服务器连接到您的 FFmpeg 环境。

  3. 开始向MCP服务器发送媒体处理任务执行。

  4. 通过提供的界面监控服务器的进度和性能。

📈 路线图

此存储库中 MCP 服务器的未来更新可能包括:

  • 与其他媒体处理工具集成。

  • 增强数据保护的安全功能。

  • 性能优化,提高处理速度。

  • 提高了处理更大工作负载的可扩展性。

🤝 贡献

如果您有兴趣为此存储库中的 MCP 服务器开发做出贡献,请遵循以下准则:

  • 分叉存储库并进行所需的更改。

  • 提交拉取请求并附上修改的详细描述。

  • 您的贡献将由存储库维护人员进行审核以确定是否可能被纳入。

📧 联系方式

如果您对此存储库中 FFmpeg 的 MCP 服务器有任何问题、反馈或建议,请随时通过developer@example.com与我们联系。


通过遵循此 README 文件,您可以快速上手ffmpeg-mcp代码库,并利用 MCP 服务器的功能完成您的媒体处理任务。如需了解更多详细信息,请浏览代码库的文件、文档和版本。感谢您对我们项目的关注!🎉

Available Tools

2 tools
extract_audioB

Extract audio as mp3 from a video

NameRequiredDescriptionDefault
input_fileYesPath to input file
output_fileNoPath to output file, output to the same directory if not specified

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. It mentions the output format (mp3) but lacks details on behavioral traits like error handling, performance constraints, or whether the operation is destructive to the input file. This leaves significant gaps for an agent to understand 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 clearly states the tool's purpose without any wasted words. It is 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.

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 (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects and usage context, leaving room for improvement in completeness.

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 both parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as format details or usage examples, resulting in a baseline score of 3.

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 audio') and the resource ('from a video'), specifying the output format as mp3. However, it doesn't differentiate from the sibling tool 'speed_up', which appears to be a different operation, so it doesn't fully distinguish from 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. The description only states what it does, with no context about prerequisites, limitations, or comparison to the sibling tool 'speed_up'.

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

speed_upC

Speed up a video

NameRequiredDescriptionDefault
input_fileYesPath to input file
max_fpsNoMax FPS for the output file
output_fileNoPath to output file, output to the same directory if not specified
speed_factorNoSpeed factor for the output file, default to 2x sped up

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 full burden for behavioral disclosure. While 'speed up' implies a transformation operation, it doesn't disclose whether this is destructive to the original file, what permissions are needed, or any rate limits. The description lacks essential behavioral context for a mutation tool.

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 at just three words, front-loading the core purpose without any wasted language. Every word earns its place in this minimal but clear statement.

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 processing tool with 4 parameters and no annotations or output schema, the description is insufficient. It doesn't explain what the tool returns, what happens to the original file, or provide any context about the processing operation beyond the basic purpose.

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 fully documents all four parameters. The description adds no additional parameter information beyond what's in the schema, meeting the baseline expectation but not providing 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 ('speed up') and resource ('a video'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'extract_audio', which handles a different video processing 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 about when to use this tool versus alternatives. The description doesn't mention the sibling tool 'extract_audio' or any other video processing options, leaving the agent without 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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv1.0.0
    • First observedextract_audio
    • First observedspeed_up

TDQS

B3.1/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: one extracts audio from video, while the other modifies video playback speed. There is no overlap in functionality, making it impossible to confuse them.

Naming Consistency5/5

Both tools follow a consistent verb_noun naming pattern (extract_audio, speed_up), using clear action verbs and descriptive nouns. The naming is uniform and predictable throughout the set.

Tool Count2/5

With only two tools, this server is severely under-scoped for an FFmpeg server, which typically handles a wide range of media processing tasks like format conversion, filtering, and metadata editing. The count feels incomplete for the domain.

Completeness1/5

The tool surface is extremely incomplete for an FFmpeg server, lacking core operations such as video format conversion, resolution changes, filtering, metadata extraction, or basic CRUD-like media processing. Agents will face significant gaps in functionality.

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