EnriVision

EnriVision

An MCP server that enables analysis of local media files, including video, audio, and documents, by uploading them to EnriProxy for server-side extraction. It supports various complex file formats and provides structured model analysis for media types often unsupported by standard MCP clients.

Category
访问服务器

README

EnriVision

EnriVision is a Model Context Protocol (MCP) server over stdio that uploads local media to EnriProxy and returns server-side extraction + model analysis.

This is useful for media types that many MCP clients cannot read reliably (videos, audio, scanned PDFs, HEIC/AVIF, large files), while keeping the MCP server itself lightweight.

What this project is

  • An MCP server process your MCP host launches (OpenCode, Claude Code, Codex, etc.)
  • A thin client for EnriProxy (resumable upload + structured output)

Requirements

  • Node.js >= 22 (recommended: Node 24 LTS)
  • A reachable EnriProxy server with these endpoints enabled:
    • POST /v1/uploads
    • HEAD /v1/uploads/:id
    • PATCH /v1/uploads/:id
    • POST /v1/vision/analyze
  • An EnriProxy API key (configured on the EnriProxy side)

Install

# Global install
npm install -g @bedolla/enrivision

# Or run without installing
npx -y @bedolla/enrivision@latest --help

Build

npm install
npm run typecheck
npm run build

Usage

1) Configure your MCP host

EnriVision runs as an MCP server over stdio. Your MCP host is responsible for launching the process.

Example: global install

{
  "EnriVision": {
    "type": "stdio",
    "command": "enrivision",
    "args": [],
    "env": {
      "ENRIPROXY_URL": "http://127.0.0.1:8787",
      "ENRIPROXY_API_KEY": "YOUR_ENRIPROXY_API_KEY",
      "ENRIVISION_DEFAULT_LANGUAGE": "es"
    }
  }
}

Example: no install (always uses whatever npm currently tags as latest)

{
  "EnriVision": {
    "type": "stdio",
    "command": "npx",
    "args": ["-y", "@bedolla/enrivision@latest"],
    "env": {
      "ENRIPROXY_URL": "http://127.0.0.1:8787",
      "ENRIPROXY_API_KEY": "YOUR_ENRIPROXY_API_KEY",
      "ENRIVISION_DEFAULT_LANGUAGE": "es"
    }
  }
}

<details> <summary>Use a local dev checkout</summary>

{
  "EnriVision": {
    "type": "stdio",
    "command": "node",
    "args": ["C:\\\\Users\\\\Administrator\\\\Projects\\\\EnriVision\\\\dist\\\\index.js"],
    "env": {
      "ENRIPROXY_URL": "http://127.0.0.1:8787",
      "ENRIPROXY_API_KEY": "YOUR_ENRIPROXY_API_KEY",
      "ENRIVISION_DEFAULT_LANGUAGE": "es"
    }
  }
}

</details>

Configuration

EnriVision is configured via environment variables:

  • ENRIPROXY_URL (string, optional, default: http://127.0.0.1:8787)
  • ENRIPROXY_API_KEY (string, required)
  • ENRIVISION_TIMEOUT_MS (string, optional, default: 1800000)
    • Parsed as an integer (milliseconds). Uploads are performed in chunks; this timeout applies per request.
  • ENRIVISION_DEFAULT_LANGUAGE (string, optional)
    • Default language to send when the tool call does not provide language.

MCP tools

EnriVision exposes this MCP tool:

  • analyze_media

<details> <summary>Tool inputs (option-by-option)</summary>

General notes:

  • The tool accepts a single JSON object as its input (the MCP arguments).
  • Exactly one of path or paths is required.
  • Paths must be absolute on the machine running the MCP server.
  • EnriVision does not accept per-call server_url/api_key overrides (these are configured via env vars).

analyze_media

Inputs:

  • path (string, optional): absolute local file path.
  • paths (string[], optional): absolute local image paths (useful for UI screenshot sets).
  • context (string, optional): high-level hint (examples: ui, diagram, chart, error, code, meeting, tutorial, photo).
  • question (string, optional): what you want to extract/answer.
  • language (string, optional): preferred response language (ISO 639-1; e.g., es, en). If omitted, uses ENRIVISION_DEFAULT_LANGUAGE when set.
  • analysis_mode (string, optional): auto | single | multipass.
  • max_frames (number, optional): single-pass video frames (1..20).
  • transcribe (boolean, optional): enable/disable transcription (videos).
  • transcription_language (string, optional): whisper hint (auto, es, en, ...).

Video targeting:

  • video.clip_start_seconds (number, optional)
  • video.clip_duration_seconds (number, optional)

Multipass tuning (advanced; used only for analysis_mode: multipass):

  • video.segment_seconds (number, optional)
  • video.max_segments (number, optional)
  • video.max_frames_per_segment (number, optional)
  • document.max_pages_total (number, optional)
  • document.pages_per_batch (number, optional)
  • document.max_images_per_batch (number, optional)
  • document.scanned_text_threshold_chars (number, optional)
  • audio.timestamps (boolean, optional)
  • audio.segment_seconds (number, optional)
  • audio.max_segments (number, optional)
  • images.max_images_total (number, optional)
  • images.images_per_batch (number, optional)
  • images.max_dimension (number, optional)

Output:

  • analysis (string): model-produced analysis.
  • media_type (string): detected media type (video, audio, image, document, image_set).
  • extraction (object): safe metadata summary (internal routing details are stripped).

Example arguments object:

{
  "path": "C:\\\\path\\\\to\\\\video.mp4",
  "question": "What are the key steps demonstrated?",
  "analysis_mode": "auto",
  "transcribe": true,
  "language": "es"
}

</details>

<details> <summary>Claude Code CLI Read(...) compatibility (reference)</summary>

Many MCP clients include a built-in Read(...) tool that can ingest local files and attach them to the model request. This is convenient, but the set of supported formats is limited and can change across client versions.

If the file you need to analyze is not reliably supported by your client (for example .avif, .heic, .svg, videos, audio, or Office documents), prefer EnriVision MCP so the client can upload bytes and EnriProxy can do extraction reliably.

</details>

<details> <summary>Supported media types (by extension)</summary>

EnriProxy determines media type using content-type and extension allow-lists.

Videos:

  • .mp4, .mov, .avi, .mkv, .webm, .m4v, .wmv, .flv, .3gp, .3g2, .ts, .mts, .m2ts, .mpeg, .mpg, .gif

Audio:

  • .mp3, .mp1, .mp2, .mpa, .mpga, .wav, .aiff, .aif, .aifc, .caf, .flac, .m4a, .m4b, .m4r, .aac, .ogg, .oga, .wma, .opus, .weba, .mka

Images:

  • .png, .apng, .jpg, .jpeg, .gif, .webp, .avif, .heic, .heif, .tiff, .tif, .bmp, .svg, .ico

Documents:

  • .pdf, .docx, .pptx, .xlsx, .jsonl

</details>

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选