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eternnoir

AI Studio MCP Server

by eternnoir
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_MODELNoGemini model to usegemini-2.5-flash
GEMINI_API_KEYYesYour Google AI Studio API key
GEMINI_TIMEOUTNoRequest timeout in milliseconds (default: 300000 = 5 minutes)300000
GEMINI_MAX_FILESNoMaximum number of files per request10
GEMINI_TEMPERATURENoTemperature for generation (0-2). Lower values produce more focused responses, higher values more creative ones0.2
GEMINI_MAX_OUTPUT_TOKENSNoMaximum output tokens8192
GEMINI_MAX_TOTAL_FILE_SIZENoMaximum total file size in MB50

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

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, preserving structure and formatting",
  "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 up to 100",
  "enable_code_execution": true
}

Combining features with thinking mode:

{
  "user_prompt": "Research quantum computing and create a Python simulation",
  "model": "gemini-2.5-pro",
  "enable_google_search": true,
  "enable_code_execution": true,
  "thinking_budget": -1
}

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.6/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'generate_content' has a clearly defined and distinct purpose.

Naming Consistency5/5

A single tool inherently has perfect naming consistency. The tool name 'generate_content' follows a clear verb_noun pattern and there are no other tools to create inconsistency.

Tool Count2/5

A single tool for an 'AI Studio MCP Server' feels too thin for the apparent scope. The tool handles multiple complex features (content generation, file processing, search, code execution), suggesting these might be better exposed as separate tools for clarity and agent usability.

Completeness2/5

The server's domain appears to be AI content generation and processing, but with only one tool, the surface is severely incomplete. There are obvious gaps for operations like listing models, managing sessions, checking status, or handling errors—common needs in such a domain that would require separate tools.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources