io.github.Headdao/slidemaster-mcp

io.github.Headdao/slidemaster-mcp

MCP (Model Context Protocol) Server for the SlideMaster Public API. This server exposes 20 tools that let any MCP-compatible AI assistant create AI-powered presentation videos from a simple topic.

Category
Visit Server

README

<!-- mcp-name: io.github.Headdao/slidemaster-mcp -->

@slidemaster/mcp-server

MCP (Model Context Protocol) Server for the SlideMaster Public API. This server exposes 20 tools that let any MCP-compatible AI assistant create AI-powered presentation videos from a simple topic.

Quick Start

1. Get an API Key

Sign in to SlideMaster and generate a key at Settings > API Keys.

2. Configure Claude Desktop

Add the following to your claude_desktop_config.json:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "slidemaster": {
      "command": "npx",
      "args": ["-y", "@slidemaster/mcp-server"],
      "env": {
        "SLIDEMASTER_API_KEY": "your-api-key-here"
      }
    }
  }
}

3. Restart Claude Desktop

After saving the config, restart Claude Desktop. You should see the SlideMaster tools available in the tool picker.

Local Development

# Install dependencies
npm install

# Build TypeScript
npm run build

# Run the server (stdio transport)
SLIDEMASTER_API_KEY=your-key npm start

Environment Variables

Variable Required Description
SLIDEMASTER_API_KEY Yes Your SlideMaster API key
SLIDEMASTER_API_BASE No Override API base URL (default: https://api.slidemaster.tw/api/v1/public)

Tools (20 total)

Content Creation

Tool Method Endpoint Description
generate_outline POST /outlines/generate Generate a presentation outline from a topic
create_project POST /projects Create a new project
upload_init POST /upload/init Initialize a file upload session (PPTX/PDF)
upload_complete POST /upload/complete Mark an upload as complete
render_slides POST /slides/render Render AI-generated slide images

Content Processing

Tool Method Endpoint Description
generate_script POST /scripts/generate Generate a narration script for one slide
batch_generate_scripts POST /scripts/batch-generate Generate scripts for all slides in a project
generate_tts POST /tts/generate Generate text-to-speech audio
generate_video POST /video/generate Compile the final video

Management

Tool Method Endpoint Description
list_projects GET /projects List all projects (paginated)
get_project GET /projects/{id} Get project details
update_project PATCH /projects/{id} Update project properties
delete_project DELETE /projects/{id} Delete a project
list_slides GET /projects/{id}/slides List slides in a project
update_slide PATCH /slides/{id} Update a slide's title or script
delete_slide DELETE /slides/{id} Delete a slide

Query & Export

Tool Method Endpoint Description
check_status GET /projects/{id}/status Check project processing status
export_project GET /projects/{id}/export Export project with download URLs
list_voices GET /voices List available TTS voices

Automation

Tool Method Endpoint Description
topic_to_video POST /pipelines/topic-to-video End-to-end: topic to finished video

Example Conversation

User: Create a 5-slide presentation about renewable energy in Taiwan

Claude: I'll create that presentation for you using SlideMaster.

[Calls generate_outline with topic="renewable energy in Taiwan", slides_count=5]

Here's the outline I generated:
1. Taiwan's Energy Landscape
2. Solar Power Expansion
3. Offshore Wind Development
4. Government Policy & Targets
5. Future Outlook

Let me now create the project and render the slides.

[Calls create_project with title="Renewable Energy in Taiwan"]
[Calls render_slides with the outline data]
[Calls batch_generate_scripts]
[Calls generate_tts]
[Calls generate_video]

Your video is being generated! Let me check the status.

[Calls check_status]

The video is ready! Here are your download links:

[Calls export_project]

- Video: https://...
- Slides: https://...

Alternatively, use the one-shot pipeline:

User: Make me a video about machine learning basics

Claude: I'll use the topic-to-video pipeline to handle everything in one step.

[Calls topic_to_video with topic="machine learning basics"]
[Polls check_status until complete]
[Calls export_project for download links]

Your video is ready!

API Documentation

Full API documentation is available at https://slidemaster.tw/api-docs.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured