ppt-engine-mcp
Drives real PowerPoint desktop application for true-fidelity PDF export and per-slide image export, complementing python-pptx by handling rendering that no library can.
README
ppt-engine-mcp
A local MCP server that drives the real PowerPoint desktop application (COM automation) to do the one thing python-pptx fundamentally cannot: render — true-fidelity PDF export and per-slide image export.
Design philosophy: this server complements library workflows instead of replacing them. Building slides and filling text is faster with python-pptx — but no library has PowerPoint's render engine. This MCP handles only the engine-exclusive part, keeping its tool surface tiny (4 tools).
Requirements
- Windows 10+ with a logged-in interactive desktop session (PowerPoint has no true headless mode)
- Microsoft Office (PowerPoint) installed and licensed — verified on Office 2016+ (PowerPoint 16.0)
- Python 3.10+ — verified on 3.12
- Claude Code or any MCP client
Install
git clone https://github.com/Feynman520/d01-p03-ppt-engine-mcp.git
cd d01-p03-ppt-engine-mcp
py -3.12 -m venv .venv # or: python -m venv .venv
.\.venv\Scripts\python.exe -m pip install -r requirements.txt
Register with Claude Code
Run this in the cloned folder (uses absolute paths, so it works from anywhere afterwards):
claude mcp add ppt-automation --scope user -- "$PWD\.venv\Scripts\python.exe" "$PWD\server.py"
--scope user makes it available in every project. Use --scope project to limit it to one project.
Verify
$py = ".\.venv\Scripts\python.exe"; $env:PYTHONUTF8 = "1"
& $py tests\smoke_com.py # COM PDF / slide image rendering / zombie cleanup
& $py tests\server_tools.py # MCP tool registration (does not launch PowerPoint)
Tools (2 core + 2 diagnostics)
| # | Tool | Input → Output | Why engine-only |
|---|---|---|---|
| ① | ppt_export_pdf |
src_path, out_path → {out_path} |
PowerPoint render engine PDF (python-pptx has no render engine) |
| ② | ppt_export_images |
src_path, out_dir, fmt?, width?, height? → {out_dir,count,files} |
Renders each slide to an image (thumbnails, previews, embedding in documents) |
| — | ppt_health |
→ {alive, powerpoint_version} |
Session check (launches PowerPoint on first call) |
| — | ppt_restart |
→ {alive} |
Recovery from COM errors |
Typical flow: build a .pptx with python-pptx → ppt_export_pdf for the distributable PDF /
ppt_export_images for slide thumbnails.
Originals are never modified; results are always written to out_path/out_dir.
Architecture notes
- Single STA worker thread (
engine/session.py): every PowerPoint call is serialized onto one dedicated thread (win32com COM objects are thread-bound; FastMCP may hop threads). - Lazy session: PowerPoint starts on the first tool call, is reused, and closes with the server.
DispatchEx+ early binding (gencache.EnsureDispatch): a dedicated instance with type-library calls. PDF viaPresentation.SaveAs(path, 32 /* ppSaveAsPDF */), images viaSlide.Export(path, "PNG", w, h).- No
Visible=False: unlike Excel/Word, PowerPoint throws when you hide the app window — instead presentations are opened windowless viaPresentations.Open(..., WithWindow=msoFalse). - Zombie prevention: PowerPoint gives no usable window handle, so the dedicated instance
PID is identified by diffing the
POWERPNT.EXEprocess list before/afterDispatchEx, and force-killed at shutdown if it survivesQuit(). - RPC-rejection retry / stdout protection: same as excel-engine-mcp.
Limitations
- Not suitable for unattended/service sessions (needs an interactive desktop).
- Slide creation/editing is faster with python-pptx — that is by design.
License
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。