Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_MODELNo默认模型gemini-3.1-pro-preview-thinking
APIYI_API_KEYYesAPI易 密钥 (必需)
APIYI_BASE_URLNoAPI易 端点https://api.apiyi.com
GEMINI_API_KEYNo备用:Google AI Studio 密钥
GEMINI_TIMEOUTNo超时时间 (ms)300000
GEMINI_BASE_URLNo备用:自定义端点
GEMINI_MAX_FILESNo最大文件数10
GEMINI_TEMPERATURENo温度参数0.2
GEMINI_MEDIA_RESOLUTIONNo媒体分辨率 (LOW/MEDIUM/HIGH)MEDIUM
GEMINI_MAX_OUTPUT_TOKENSNo最大输出 tokens8192
GEMINI_MAX_TOTAL_FILE_SIZENo最大总文件大小 (MB)50

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_contentA

Generate content using Gemini with optional file inputs, code execution, and Google search. Supports multiple files: images (JPG, PNG, GIF, WebP, SVG, BMP, TIFF), video (MP4, AVI, MOV, WebM, FLV, MPG, WMV), audio (MP3, WAV, AIFF, AAC, OGG, FLAC), documents (PDF), and text files (TXT, MD, JSON, XML, CSV, HTML). MIME type is auto-detected from file extension.

Example usage:

{
  "user_prompt": "Analyze this video",
  "files": [{"path": "/path/to/video.mp4"}]
}

PDF to Markdown conversion:

{
  "user_prompt": "Convert this PDF to well-formatted Markdown",
  "files": [{"path": "/document.pdf"}]
}

With Google Search:

{
  "user_prompt": "What are the latest AI breakthroughs in 2024?",
  "enable_google_search": true
}

With Code Execution:

{
  "user_prompt": "Write and run a Python script to calculate prime numbers",
  "enable_code_execution": true
}

Media Resolution Optimization (save tokens):

{
  "user_prompt": "Describe this image",
  "files": [{"path": "/image.jpg"}],
  "media_resolution": "LOW"
}
generate_content_batchA

Generate multiple contents concurrently using Gemini. This tool allows you to send multiple requests in parallel for better performance.

Each request in the batch requires a unique 'id' field to identify results. All other parameters are the same as generate_content.

Example usage:

{
  "requests": [
    {
      "id": "req1",
      "user_prompt": "Describe image 1",
      "files": [{"path": "/image1.jpg"}]
    },
    {
      "id": "req2", 
      "user_prompt": "Describe image 2",
      "files": [{"path": "/image2.jpg"}]
    },
    {
      "id": "req3",
      "user_prompt": "Summarize this document",
      "files": [{"path": "/doc.pdf"}]
    }
  ],
  "max_concurrency": 5
}

The response includes success/failure status for each request:

{
  "total": 3,
  "succeeded": 2,
  "failed": 1,
  "results": [
    {"id": "req1", "success": true, "content": "..."},
    {"id": "req2", "success": true, "content": "..."},
    {"id": "req3", "success": false, "error": "..."}
  ]
}

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/2799662352/apiyi-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server