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 MCP Hub Showcase • 📦 GenPark Official Website • 📖 Documentation
genpark-speech-filler-word-remover-cleaner-skill is a deterministic, zero-dependency Python skill engineered for autonomous shortform video editing, audio silence pacing, generative canvas tiling, and viral hook optimization.
Executive Capability: Transcript timestamp-aligned speech filler word remover & cutlist generator (Descript / Cleanvoice)
🐍 Zero External pip Dependencies: Runs instantaneously on standard Python 3.9+ with zero environment bloat.
🔌 Native Model Context Protocol (MCP): Seamlessly integrates into Claude Desktop, Cursor IDE, CapCut bot automations, and viral video agent pipelines.
🎯 Deterministic & Reliable: 100% predictable input/output contracts with full JSON Schema validation.
🚀 Low Latency: Sub-millisecond execution overhead tailored for high-concurrency batch media processing.
Related MCP server: genpark-speech-filler-word-remover-cleaner-skill
graph LR
User([🎬 Video Creator / Media Swarm]) -->|Audio/Video Telemetry & Transcript| MCP[⚡ MCP Server / Protocol]
MCP --> Client[🛠️ Media Processing Kernel]
Client --> Engine[🧠 Pacing & Reframing Pipeline]
Engine --> Cuts[✂️ Precise Cut-Lists & Telemetry Dossier]
Cuts --> Userpython example_usage.pyfrom client import SpeechFillerWordRemoverCleanerClient
client = SpeechFillerWordRemoverCleanerClient()
result = client.detect_and_clean_fillers()
print(result)Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json{
"mcpServers": {
"genpark-speech-filler-word-remover-cleaner-skill": {
"command": "python",
"args": ["/path/to/genpark-speech-filler-word-remover-cleaner-skill/mcp_server.py"]
}
}
}Parameter | Type | Required | Description |
|
| Yes | Primary input parameter parsed and executed deterministically |
|
| Yes | Standardized response schema containing execution telemetry |
GenPark AI Agent Skills are engineered with zero external dependencies using pure Python standard library code. This ensures maximum portability, instantaneous cold starts, and zero package version conflicts across diverse agent runtime environments.
Explore the comprehensive directory of 1,200+ open-source, production-ready AI Agent skills at the GenPark AI MCP Hub and learn more about multimedia AI tools at GenPark AI.
Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.
Transcript-based audio editing: transcribe audio, edit by word ID, export edited audio.
Compose, edit and render video with your AI agent. Turn footage into finished edits with content-aware reframing, word-timed captions and motion graphics. Hosted MCP with OAuth sign-in; cloud processing uses credits.
Valmera — the world’s most advanced AI video editor. Edit recorded tutorials, podcasts, interviews and webinars through Claude, ChatGPT or another compatible MCP client. Cut footage, add captions, reframe, review a preview, revise specific sections and export MP4. Hosted editing with OAuth; an eligible paid Valmera plan is required.
AI video editor for agents and humans: timeline, captions, color, audio and generation as MCP tools.
