Google AI Studio▌

by eternnoir
Leverage Google AI Studio & Gemini API to process images, videos, audio, PDFs, & text for document conversion, analysis
Integrates with Google AI Studio/Gemini API to process multimodal content including images, videos, audio, PDFs, and text files for content generation, analysis, and document conversion tasks.
best for
- / Content creators analyzing multimedia assets
- / Document processing and analysis workflows
- / Developers building AI-powered applications
- / Research teams working with mixed media content
capabilities
- / Generate text content using Gemini models
- / Analyze images, videos, and audio files
- / Process PDF and Office documents
- / Set custom system prompts for AI behavior
- / Handle multiple files in a single request
- / Configure model parameters like temperature and output tokens
what it does
Connects to Google AI Studio/Gemini API to generate and analyze content from text, images, videos, audio, PDFs, and other file formats. Requires a Google AI Studio API key.
about
Google AI Studio is a community-built MCP server published by eternnoir that provides AI assistants with tools and capabilities via the Model Context Protocol. Leverage Google AI Studio & Gemini API to process images, videos, audio, PDFs, & text for document conversion, analysis It is categorized under ai ml.
how to install
You can install Google AI Studio in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Google AI Studio is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
AI Studio MCP Server
A Model Context Protocol (MCP) server that integrates with Google AI Studio / Gemini API, providing content generation capabilities with support for files, conversation history, and system prompts.
Installation and Usage
Prerequisites
- Node.js 20.0.0 or higher
- Google AI Studio API key
Using npx (Recommended)
GEMINI_API_KEY=your_api_key npx -y aistudio-mcp-server
Local Installation
npm install -g aistudio-mcp-server
GEMINI_API_KEY=your_api_key aistudio-mcp-server
Configuration
Set your Google AI Studio API key as an environment variable:
export GEMINI_API_KEY=your_api_key_here
Optional Configuration
GEMINI_MODEL: Gemini model to use (default: gemini-2.5-flash)GEMINI_TIMEOUT: Request timeout in milliseconds (default: 300000 = 5 minutes)GEMINI_MAX_OUTPUT_TOKENS: Maximum output tokens (default: 8192)GEMINI_MAX_FILES: Maximum number of files per request (default: 10)GEMINI_MAX_TOTAL_FILE_SIZE: Maximum total file size in MB (default: 50)GEMINI_TEMPERATURE: Temperature for generation (0-2, default: 0.2)
Example:
export GEMINI_API_KEY=your_api_key_here
export GEMINI_MODEL=gemini-2.5-flash
export GEMINI_TIMEOUT=600000 # 10 minutes
export GEMINI_MAX_OUTPUT_TOKENS=16384 # More output tokens
export GEMINI_MAX_FILES=5 # Limit to 5 files per request
export GEMINI_MAX_TOTAL_FILE_SIZE=100 # 100MB limit
export GEMINI_TEMPERATURE=0.7 # More creative responses
Available Tools
generate_content
Generates content using Gemini with comprehensive support for files, conversation history, and system prompts. Supports various file types including images, PDFs, Office documents, and text files.
Parameters:
user_prompt(string, required): User prompt for generationsystem_prompt(string, optional): System prompt to guide AI behaviorfiles(array, optional): Array of files to include in generation- Each file object must have either
pathorcontent path(string): Path to filecontent(string): Base64 encoded file contenttype(string, optional): MIME type (auto-detected from file extension)
- Each file object must have either
model(string, optional): Gemini model to use (default: gemini-2.5-flash)temperature(number, optional): Temperature for generation (0-2, default: 0.2). Lower values produce more focused responses, higher values more creative ones
Supported file types (Gemini 2.5 models):
- Images: JPG, JPEG, PNG, GIF, WebP, SVG, BMP, TIFF
- Video: MP4, AVI, MOV, WEBM, FLV, MPG, WMV (up to 10 files per request)
- Audio: MP3, WAV, AIFF, AAC, OGG, FLAC (up to 15MB per file)
- Documents: PDF (treated as images, one page = one image)
- Text: TXT, MD, JSON, XML, CSV, HTML
File limitations:
- Maximum file size: 15MB per audio/video/document file
- Maximum total request size: 20MB (2GB when using Cloud Storage)
- Video files: Up to 10 per request
- PDF files follow image pricing (one page = one image)
Basic example:
{
"user_prompt": "Analyze this image and describe what you see",
"files": [
{
"path": "/path/to/image.jpg"
}
]
}
PDF to Markdown conversion:
{
"user_prompt": "Convert this PDF to well-formatted Markdown, preserving structure and formatting. Return only the Markdown content.",
"files": [
{
"path": "/path/to/document.pdf"
}
]
}
With system prompt:
{
"system_prompt": "You are a helpful document analyst specialized in technical documentation",
"user_prompt": "Please provide a detailed explanation of the authentication methods shown in this document",
"files": [
{"path": "/api-docs.pdf"}
]
}
Multiple files example:
{
"user_prompt": "Compare these documents and images",
"files": [
{"path": "/document.pdf"},
{"path": "/chart.png"},
{"content": "base64encodedcontent", "type": "image/jpeg"}
]
}
Common Use Cases
PDF to Markdown Conversion
To convert PDF files to Markdown format, use the generate_content tool with an appropriate prompt:
{
"user_prompt": "Convert this PDF to well-formatted Markdown, preserving structure, headings, lists, and formatting. Include table of contents if the document has sections.",
"files": [
{
"path": "/path/to/document.pdf"
}
]
}
Image Analysis
Analyze images, charts, diagrams, or photos with detailed descriptions:
{
"system_prompt": "You are an expert image analyst. Provide detailed, accurate descriptions of visual content.",
"user_prompt": "Analyze this image and describe what you see. Include details about objects, people, text, colors, and composition.",
"files": [
{
"path": "/path/to/image.jpg"
}
]
}
For screenshots or technical diagrams:
{
"user_prompt": "Describe this system architecture diagram. Explain the components and their relationships.",
"files": [
{
"path": "/architecture-diagram.png"
}
]
}
Audio Transcription
Generate transcripts from audio files:
{
"system_prompt": "You are a professional transcription service. Provide accurate, well-formatted transcripts.",
"user_prompt": "Please transcribe this audio file. Include speaker identification if multiple speakers are present, and format it with proper punctuation and paragraphs.",
"files": [
{
"path": "/meeting-recording.mp3"
}
]
}
For interview or meeting transcripts:
{
"user_prompt": "Transcribe this interview and provide a summary of key points discussed.",
"files": [
{
"path": "/interview.wav"
}
]
}
MCP Client Configuration
Add this server to your MCP client configuration:
{
"mcpServers": {
"aistudio": {
"command": "npx",
"args": ["-y", "aistudio-mcp-server"],
"env": {
"GEMINI_API_KEY": "your_api_key_here",
"GEMINI_MODEL": "gemini-2.5-flash",
"GEMINI_TIMEOUT": "600000",
"GEMINI_MAX_OUTPUT_TOKENS": "16384",
"GEMINI_MAX_FILES": "10",
"GEMINI_MAX_TOTAL_FILE_SIZE": "50",
"GEMINI_TEMPERATURE": "0.2"
}
}
}
}
Development
Setup
Make sure you have Node.js 20.0.0 or higher installed.
npm install
npm run build
Running locally
GEMINI_API_KEY=your_api_key npm run dev
License
MIT
FAQ
- What is the Google AI Studio MCP server?
- Google AI Studio is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Google AI Studio?
- This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Ratings
4.5★★★★★10 reviews- ★★★★★Shikha Mishra· Oct 10, 2024
Google AI Studio is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Piyush G· Sep 9, 2024
We evaluated Google AI Studio against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: Google AI Studio is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Sakshi Patil· Jul 7, 2024
Google AI Studio reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Ganesh Mohane· Jun 6, 2024
I recommend Google AI Studio for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: Google AI Studio surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Dhruvi Jain· Apr 4, 2024
Google AI Studio has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Mar 3, 2024
According to our notes, Google AI Studio benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Pratham Ware· Feb 2, 2024
We wired Google AI Studio into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Yash Thakker· Jan 1, 2024
Google AI Studio is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.