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PPTAgent MCP Server

icip-cas/PPTAgent

Score: 91.0 Rank #283 Agent Framework
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An Agentic Framework for Reflective PowerPoint Generation

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Overview

icip-cas/PPTAgent is a Python tool licensed under MIT. An Agentic Framework for Reflective PowerPoint Generation Topics: agent, llm, presentation, slide, agentic-ai, mcp, openclaw.

Ranked #283 out of 24840 indexed tools.

In the top 2% of all indexed tools.

Has 5,060 GitHub stars.

Has 27 contributors.

Actively maintained with commits in the last week.

Ecosystem

Python MIT 634 pypi/wk
agentllmpresentationslideagentic-aimcpopenclaw

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 5,060

5,060 stars → well-known project

Freshness 25% 3d ago

Last commit 3d ago → actively maintained

Issue Health 25% 90%

123/136 issues closed → responsive maintainer

Contributors 10% 27

27 contributors → active community

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads 13% 634/wk

634 weekly installs → early adoption

Forks 592
Description Good
License MIT

Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →

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AgentRank score for icip-cas/PPTAgent
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Matched Queries

topic:mcp

From the README

<h1 align="center">
  
</h1>

> [!TIP]
> **PPTAgent Skill for Claude Code, Codex & OpenCode Now Available!**
>
> Create, revise, and visually review editable PowerPoint decks with your coding agent.
>
> **[Install the Skill →](#install-skill)** · **[Use Atria Dawn Preview →](#quick-start)**
>
> **Free Token Plan:** [Discovery](https://discovery-home.intern-ai.org.cn/) · [Atria API](https://api.atria-asi.ai/)
>
> You can use a multimodal vision model as a multimodal reviewer and apply for an API token through the [Duanyan (端砚) Token Plan](https://discovery.intern-ai.org.cn/token-plan/home?tabIndex=1). We recommend `deepseek-v4-flash-vision` as the multimodal model. [Setup guide →](skills/pptagent/README.md#visual-review)

> [!IMPORTANT]
> **Looking for the previous runtime or reproducing the research papers?** Use
> these pinned versions instead of the current development branch:
>
> - **PPTAgent (EMNLP 2025):** [paper](https://arxiv.org/abs/2501.03936) · [code at v0.2.0](https://github
Read full README on GitHub →

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