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Video Convert MCP

by pickstar-2002
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TypeScript
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🎬 Video Convert MCP

NPM Version License Node.js Downloads

一款基于 MCP (Model Context Protocol) 协议的强大、高效的视频格式转换工具。支持在 AI 编程助手中直接进行视频格式转换，让视频处理变得前所未有的简单。

✨ 功能特性

  • 🚀 多格式转换: 支持 MP4、AVI、MOV、WMV、MKV、WEBM、M4V 等主流视频格式之间的相互转换

  • ⚡ 批量处理: 一次性处理多个视频文件，大幅提升工作效率

  • 📊 质量控制: 提供 low、medium、high、ultra 四档质量预设，完美平衡文件大小和画质

  • 🔧 详细信息: 轻松获取视频的详细元数据，如格式、分辨率、时长、码率等

  • 🔒 类型安全: 使用 TypeScript 开发，提供完整的类型定义，确保调用安全

  • 📦 零配置: 内置 FFmpeg，用户无需在本地安装任何额外依赖，开箱即用

Related MCP server: Video MCP Server

🛠️ 安装与配置

本工具是一个 MCP 服务，无需全局安装。您只需在支持 MCP 的 AI 编程助手（如 CodeBuddy、Cursor、Claude Desktop 等）中进行配置即可使用。

CodeBuddy 配置

打开 CodeBuddy 的 MCP 配置文件 codebuddy_mcp_settings.json，在 mcpServers 对象中添加以下配置：

{
  "mcpServers": {
    "video-convert": {
      "timeout": 60,
      "type": "stdio",
      "command": "npx",
      "args": [
        "@pickstar-2002/video-convert-mcp@latest"
      ]
    }
  }
}

Cursor 配置

在 Cursor 的设置中找到 MCP 配置，添加：

{
  "mcpServers": {
    "video-convert": {
      "command": "npx",
      "args": ["@pickstar-2002/video-convert-mcp@latest"]
    }
  }
}

Claude Desktop 配置

编辑 claude_desktop_config.json 文件：

{
  "mcpServers": {
    "video-convert": {
      "command": "npx",
      "args": ["@pickstar-2002/video-convert-mcp@latest"]
    }
  }
}

💡 推荐使用 @latest 标签来确保您总能使用最新的稳定版本。

🚨 疑难解答 (Troubleshooting)

常见问题 1: Connection closed 错误

问题: 遇到 MCP error -32000: Connection closed 或类似的连接错误。

原因: 这通常是 npx 的缓存问题导致的。如果您之前运行过旧版本的包，npx 可能会继续使用缓存中的旧版本。

解决方案 (按推荐顺序)：

  1. 首选方案: 确认使用了 @latest 标签

    "args": ["@pickstar-2002/video-convert-mcp@latest"]

  2. 备用方案: 锁定到特定的稳定版本号

    "args": ["@pickstar-2002/video-convert-mcp@1.2.1"]

  3. 终极方案: 清理 npx 缓存

    # Windows
npm config get cache
# 然后删除缓存目录中的 _npx 文件夹

# macOS/Linux
rm -rf ~/.npm/_npx

常见问题 2: FFmpeg 相关错误

问题: 提示找不到 FFmpeg 或 FFmpeg 执行失败。

解决方案: 本工具内置了 FFmpeg，通常不会出现此问题。如果遇到，请尝试：

  • 重启您的 AI 编程助手

  • 检查网络连接（首次运行时需要下载依赖）

常见问题 3: 权限错误

问题: 在某些系统上可能遇到权限相关的错误。

解决方案:

  • 确保输出目录有写入权限

  • 在 Windows 上，尝试以管理员身份运行您的 AI 编程助手

📖 API 文档

本 MCP 服务提供了以下工具：

convert_video

转换单个视频文件为指定格式。

参数:

  • inputPath (string, 必填): 输入视频文件的完整路径

  • outputFormat (string, 必填): 目标输出格式，支持: mp4, avi, mov, wmv, mkv, webm, m4v

  • outputPath (string, 可选): 输出文件路径，不指定则自动生成

  • quality (string, 可选): 视频质量预设 (low, medium, high, ultra)

  • resolution (string, 可选): 输出分辨率，格式为 "宽度x高度"，如 "1920x1080"

  • videoBitrate (number, 可选): 视频码率，单位 kbps

  • audioBitrate (number, 可选): 音频码率，单位 kbps

  • frameRate (number, 可选): 输出帧率，单位 fps

  • overwrite (boolean, 可选): 是否覆盖已存在的输出文件，默认 false

示例:

// 基本转换
convert_video({
  inputPath: "/path/to/input.avi",
  outputFormat: "mp4"
})

// 高质量转换
convert_video({
  inputPath: "/path/to/input.mov",
  outputFormat: "mp4",
  quality: "high",
  resolution: "1920x1080"
})

batch_convert

批量转换多个视频文件。

参数:

  • inputFiles (string[], 必填): 输入视频文件路径数组

  • outputFormat (string, 必填): 目标输出格式

  • outputDir (string, 必填): 输出目录路径

  • quality (string, 可选): 视频质量预设

  • overwrite (boolean, 可选): 是否覆盖已存在的输出文件

示例:

batch_convert({
  inputFiles: [
    "/path/to/video1.avi",
    "/path/to/video2.mov",
    "/path/to/video3.wmv"
  ],
  outputFormat: "mp4",
  outputDir: "/path/to/output",
  quality: "high"
})

get_video_info

获取视频文件的详细信息。

参数:

  • filePath (string, 必填): 视频文件的完整路径

返回信息:

  • 文件格式和编解码器信息

  • 视频分辨率、帧率、码率

  • 音频采样率、声道数、码率

  • 文件大小和时长

  • 元数据信息

示例:

get_video_info({
  filePath: "/path/to/video.mp4"
})

🎯 使用示例

基本转换

请帮我将 /Users/john/Desktop/video.avi 转换为 MP4 格式

批量转换

请将 /Users/john/Videos/ 目录下的所有 AVI 文件批量转换为 MP4 格式，输出到 /Users/john/Converted/ 目录

获取视频信息

请帮我查看 /Users/john/movie.mp4 的详细信息

高质量转换

请将 /Users/john/raw_video.mov 转换为高质量的 MP4 格式，分辨率设置为 1920x1080

🤝 贡献指南

欢迎各种形式的贡献！如果您有任何想法、建议或发现了 bug，请随时参与到项目中来。

如何贡献

  1. Fork 本仓库

  2. 创建您的特性分支 (git checkout -b feature/AmazingFeature)

  3. 提交您的更改 (git commit -m 'Add some AmazingFeature')

  4. 推送到分支 (git push origin feature/AmazingFeature)

  5. 打开一个 Pull Request

开发环境设置

# 克隆仓库
git clone https://github.com/pickstar-2002/video-convert-mcp.git
cd video-convert-mcp

# 安装依赖
npm install

# 开发模式运行
npm run dev

# 构建项目
npm run build

📄 许可证

本项目使用 MIT 许可证。详情请查看 LICENSE 文件。

🔗 相关链接

📧 联系作者

如果您有任何问题、建议或合作意向，欢迎联系我！

微信: pickstar_loveXX

⭐ 如果这个项目对您有帮助，请给个 Star 支持一下！⭐

Made with ❤️ by pickstar-2002

Available Tools

3 tools
batch_convertB

批量转换多个视频文件为指定格式。支持同时处理多个文件，提高转换效率。

ParametersJSON Schema
NameRequiredDescriptionDefault
inputFilesYes输入视频文件路径列表
outputFormatYes目标输出格式
outputDirYes输出目录路径
qualityNo视频质量预设（可选）
overwriteNo是否覆盖已存在的输出文件（默认false）

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 full burden. It mentions batch processing and efficiency but lacks critical behavioral details: whether this is a long-running operation, if it requires specific permissions, what happens on failure, if files are modified in-place, or what the output looks like. For a mutation tool with zero annotation coverage, this is insufficient disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences that each add value. The first sentence states the core purpose, the second adds context about batch efficiency. No wasted words, though it could be slightly more structured with clearer separation of purpose vs benefits.

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 incomplete. It doesn't address behavioral aspects like error handling, performance characteristics, side effects, or what constitutes successful completion. The agent would need to guess about important operational details.

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 parameters are well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions '指定格式' (specified format) which aligns with 'outputFormat' but provides no additional context. Baseline 3 is appropriate when 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 tool's purpose: '批量转换多个视频文件为指定格式' (batch convert multiple video files to specified format). It specifies the verb (convert), resource (video files), and scope (multiple files). However, it doesn't explicitly distinguish from sibling tools like 'convert_video' - it mentions batch processing but doesn't clarify if 'convert_video' is for single files.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: '支持同时处理多个文件，提高转换效率' (supports processing multiple files simultaneously, improving conversion efficiency). This suggests using this tool for batch operations rather than single files, but doesn't explicitly state when to use this vs 'convert_video' or mention any prerequisites, exclusions, or alternatives.

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

convert_videoC

将视频文件转换为指定格式。支持MP4、AVI、MOV、WMV、FLV、MKV、WEBM、M4V等主流格式之间的相互转换。

ParametersJSON Schema
NameRequiredDescriptionDefault
inputPathYes输入视频文件的完整路径
outputFormatYes目标输出格式
outputPathNo输出文件路径（可选，如果不指定则自动生成）
qualityNo视频质量预设（可选）
resolutionNo输出分辨率，格式为"宽度x高度"，如"1920x1080"（可选）
videoBitrateNo视频码率，单位kbps（可选）
audioBitrateNo音频码率，单位kbps（可选）
frameRateNo输出帧率，单位fps（可选）
overwriteNo是否覆盖已存在的输出文件（默认false）

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. It states the conversion function but lacks critical behavioral details: whether it's a read/write operation, if it modifies source files, what happens on failure, performance characteristics, or output location behavior. The description doesn't compensate for the missing annotations.

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 - a single sentence that efficiently states the core function and lists supported formats. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for a conversion 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?

For a complex video conversion tool with 9 parameters, no annotations, and no output schema, the description is insufficient. It doesn't address behavioral aspects, error conditions, performance implications, or provide usage context. The agent would struggle to understand when and how to use this tool effectively beyond basic parameter passing.

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 9 parameters thoroughly. The description adds minimal value beyond the schema by listing format examples, but doesn't provide additional semantic context about parameter interactions, defaults, or constraints. Baseline 3 is appropriate when 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 tool's purpose: '将视频文件转换为指定格式' (convert video files to specified format). It specifies the action (convert) and resource (video files), and lists supported formats. However, it doesn't explicitly differentiate from sibling tools like batch_convert or get_video_info, which prevents 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?

The description provides no guidance on when to use this tool versus alternatives like batch_convert (for multiple files) or get_video_info (for metadata extraction). It mentions supported formats but doesn't specify any context, prerequisites, or exclusions for usage.

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

get_video_infoC

获取视频文件的详细信息，包括格式、分辨率、时长、编解码器、码率等。

ParametersJSON Schema
NameRequiredDescriptionDefault
filePathYes视频文件的完整路径

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. While it indicates this is an information retrieval operation ('获取' meaning 'get'), it doesn't address important behavioral aspects like whether this requires file system access permissions, what happens if the file doesn't exist or is inaccessible, whether there are rate limits, or what the response format looks like. For a file operation tool with zero annotation coverage, this represents significant gaps in behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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 and enumerates the types of information it retrieves. There's no wasted language or unnecessary elaboration. While it could potentially benefit from more context about usage or behavior, what's present is well-structured and front-loaded with the core purpose.

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?

For a single-parameter read operation with no output schema, the description provides adequate but minimal coverage. It clearly states what information the tool retrieves, which is helpful context given the lack of output schema. However, with no annotations and sibling tools present, it should ideally provide more guidance about when to use this versus alternatives and address behavioral aspects like error conditions or access requirements.

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 input schema has 100% description coverage, with the single parameter 'filePath' clearly documented as '视频文件的完整路径' (complete path to the video file). The description doesn't add any parameter-specific information beyond what the schema already provides, nor does it need to since schema coverage is complete. This meets the baseline expectation when the schema handles parameter documentation effectively.

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 as retrieving detailed information about video files, specifying the types of information included (format, resolution, duration, codec, bitrate). It uses specific verbs ('获取' meaning 'get/retrieve') and identifies the resource ('视频文件' meaning 'video file'). However, it doesn't explicitly differentiate from sibling tools like batch_convert or convert_video, which appear to be transformation tools rather than information retrieval tools.

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. While the purpose suggests it's for retrieving metadata rather than converting videos (which the sibling tools appear to do), there's no explicit comparison or context about when this tool is appropriate versus when other tools might be needed. The description simply states what the tool does without usage context.

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. Dates show when Glama detected each change.

  1. 3 tool updates
    • First observedbatch_convert
    • First observedconvert_video
    • First observedget_video_info
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TDQS

B3.1/5.0
Disambiguation3/5

The tools have some overlap in purpose, particularly between batch_convert and convert_video, which both handle video format conversion. However, the descriptions help clarify that batch_convert is for multiple files while convert_video is for single files, reducing confusion. get_video_info is clearly distinct for metadata retrieval.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case, such as batch_convert, convert_video, and get_video_info. This predictable naming makes it easy for agents to understand and use the tools without confusion.

Tool Count3/5

With only 3 tools, the count feels thin for a video conversion server, as it lacks operations like update, delete, or more advanced processing. However, it covers basic conversion and info retrieval, making it borderline but not severely mismatched.

Completeness2/5

There are significant gaps in the tool surface for a video conversion domain. Missing operations include editing videos (e.g., trim, merge), managing conversion jobs (e.g., cancel, list), and handling audio or subtitle tracks, which could lead to agent failures in complex workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

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