genpark-enterprise-slide-deck-narrative-compiler-skill
Supports consumer agentic commerce use cases such as Expedia by transforming source material into structured executive slide deck narratives with layout templates, card callouts, and speaker notes.
Supports consumer agentic commerce use cases such as Mastercard Agent Connect by generating structured slide deck narratives, card callouts, speaker notes, and timing budgets from enterprise inputs.
Targeted for consumer agentic commerce workflows involving Meta Muse, enabling compilation of enterprise documents, meeting transcripts, and KPI metrics into structured executive slide decks with speaker notes and timing budgets.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
genpark-enterprise-slide-deck-narrative-compiler-skill
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
🌟 Overview
genpark-enterprise-slide-deck-narrative-compiler-skill delivers robust, industrial-grade capabilities engineered for Consumer Agentic Commerce (e.g. Meta Muse, Expedia, Mastercard Agent Connect) and Enterprise Workplace Execution (e.g. Tencent WorkBuddy Goal-to-PPT/Excel deliverable workflows). Built exclusively on the Python standard library with zero external runtime dependencies, it integrates seamlessly as a native Model Context Protocol (MCP) server or an importable Python module.
Enterprise Presentation & Slide Deck Narrative Structure Compiler (inspired by Tencent WorkBuddy Goal-to-PPT Workflows). Transforms raw enterprise documents, meeting transcripts, and KPI metrics into structured executive slide decks with layout templates, card callouts, speaker notes, and timing budgets.
💡 Key Capabilities
Zero-Dependency Architecture: Runs anywhere Python 3.9+ is installed without
pip installoverhead or supply-chain vulnerabilities.Model Context Protocol (MCP) First: Compatible with Claude Desktop, Cursor, GenPark Engine, Meta Muse, and enterprise managed agent runtimes.
Deterministic & Safe: Rigorous state machine models, cryptographic ledger hashes, mathematical dependency graphs, and full telemetry.
High Concurrency & Low Latency: In-memory caching, topological cycle detection, and optimized execution loops.
Related MCP server: mulmocast-vision
🚀 Quickstart
1. Direct Python Usage
from client import EnterpriseSlideDeckNarrativeCompiler
client = EnterpriseSlideDeckNarrativeCompiler()
result = client.compile_deck_structure()
print(result)2. Standalone MCP Server Execution
Run the MCP server via standard JSON-RPC 2.0 stdio:
python mcp_server.pyVerify standard compliance and self-tests:
python mcp_server.py --test3. Claude Desktop / Cursor MCP Configuration
Add this tool to your claude_desktop_config.json or Cursor MCP settings:
{
"mcpServers": {
"genpark-enterprise-slide-deck-narrative-compiler-skill": {
"command": "python",
"args": ["/absolute/path/to/genpark-enterprise-slide-deck-narrative-compiler-skill/mcp_server.py"]
}
}
}🛠️ Verification & Testing
Run the included verification suite:
python example_usage.py📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
Developed with ❤️ by the GenPark Autonomous Agent Ecosystem Team.
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