by ykuwai · MCP Server · ★ 80
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ppt-mcp safe to install? View the security audit →
日本語版はこちら Real-time PowerPoint control through COM automation —an MCP server with 156 tools for AI agents and developers. An MCP (Model Context Protocol) server that gives AI agents full control over a live Microsoft PowerPoint instance via COM automation. Unlike file-based libraries like python-pptx, this server interacts directly with a running PowerPoint application. 🎬 Demo An agent building a deck in a live PowerPoint window (15x speed): https://github.com/user-attachments/assets/178b9b5b-624d-4de0-a1dd-619dc13d4bd7 ✨ Key Features Real-time control — Directly manipulates a running PowerPoint instance; changes appear instantly on screen 156 t
claude mcp add powerpoint uvx ppt-mcp
claude mcp add --scope project powerpoint uvx ppt-mcpTaken from the project's README on GitHub. Check the security audit before running it.
No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
| Stars | 80 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 64/100 |
| Open Issues | 8 |
| Last Updated | 2026-09-24 |
| Created | 2026-02-16 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
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ppt-mcp is The world's best PowerPoint MCP server. Real-time control of a live PowerPoint on Windows and macOS, 156 tools for AI agents. It is categorized as a MCP Server with 80 GitHub stars.
ppt-mcp is primarily written in Python. It covers topics such as ai-agents, apple-events, com-automation.
The README on GitHub (github.com/ykuwai/ppt-mcp) gives: claude mcp add powerpoint uvx ppt-mcp , then claude mcp add --scope project powerpoint uvx ppt-mcp. Usage details are in the same README.
The top alternatives to ppt-mcp on Agent Skills Hub include daymon, toolhive-studio, Mck-ppt-design-skill. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: