Frame Pulse MCP
Provides AI agents with real-time system monitoring and control for creative workstations, enabling thermal management and process prioritization to prevent crashes.
README
in progress
🎬 Frame Pulse MCP
AI-native telemetry for creative workstations.
Give your AI assistant (Claude, Hermes, Cursor) a "nervous system" to monitor and govern heavy creative workloads—Blender renders, Unreal builds, Houdini simulations—preventing thermal crashes and lost work during crunch.

🎯 The Problem Frame Pulse Solves
Digital content creation (DCC) tools are resource-intensive. During overnight renders or UE5 lighting builds, workstations overheat, hang, or crash—destroying hours of work and missing deadlines.
Existing tools (Glances, htop) show data. Frame Pulse lets AI act.
| Traditional Monitoring | Frame Pulse with AI |
|---|---|
| You watch numbers | Claude asks "Is my system safe?" |
| Crash after the fact | Throttle before thermal damage |
| Manual Task Manager | Natural language "deprioritize Chrome" |
| Silent failure | Discord/Telegram alerts at 2AM |
🚀 Quick Start
Option A: Claude Desktop (Recommended)
- Clone and install
git clone [https://github.com/idaakiwumi/frame-pulse-mcp.git](https://github.com/idaakiwumi/frame-pulse-mcp.git)
cd frame-pulse-mcp
pip install -r requirements.txt
- Add to Claude Desktop config
-
Windows (MSIX/Store):
%LOCALAPPDATA%\Packages\Claude_pzs8sxrjxfjjc\LocalCache\Roaming\Claude\claude_desktop_config.json -
**Other possible paths
\AppData\Roaming\Claude\claude_desktop_config.json\AppData\Local\Claude\claude_desktop_config.json -
Standard:
%APPDATA%\Claude\claude_desktop_config.json
-
{
"mcpServers": {
"frame-pulse": {
"command": "py",
"args": [
"-3.14",
"-u",
"C:\\Users\\YOUR_PATH\\frame-pulse-mcp\\src\\frame_pulse\\server.py"
]
}
}
}
Then ask Claude: "Check my system status" or "Deprioritize my background apps"
Option B: The "Hero Demo" (Streamlit)
I built a high-fidelity Mission Control Dashboard using Streamlit. While the MCP runs in the background, this dashboard serves as the visual command center for the project.
streamlit run streamlit_app/mission_control.py
📱 The "Digital Pager" Ecosystem (Telegram & Discord)
As a Product Architect, I designed Frame Pulse to be "Headless." Creative professionals don't want another window to monitor; they want an assistant that pings them when they are away from their desk.
- Telegram Bot: Acts as a private production pager. Get a message on your phone if your CPU hits 90°C while you're grabbing coffee.
- Discord Webhooks: Rich, color-coded embeds sent to your studio's Discord server for team-wide render farm monitoring.
Setup: Configure your .env file with your TELEGRAM_BOT_TOKEN and TELEGRAM_CHAT_ID.
🛠️ MCP Tools for AI Agents
| Tool | Function | Use Case |
|---|---|---|
check_system_health() |
CPU, RAM, and Thermal scan | "Is it safe to start a 6-hour render?" |
scan_creative_apps() |
Identifies Blender, Unreal, Maya, etc. | "What's currently taxing the GPU?" |
emergency_throttle() |
Immediate CPU priority reduction | "CRITICAL: Throttle background apps now." |
get_thermal_status() |
Real-time temperature read | "Am I at risk of a thermal shutdown?" |
🤝 Community & Recognition
**Featured on Lobehub — AI tools discovery platform.
🛠️ Built With
- MCP — Model Context Protocol for AI tool interoperability
- FastMCP — Python SDK for MCP servers
- psutil — Cross-platform system monitoring
- Streamlit — Rapid Python dashboarding
📸 Demo
[30-second GIF: Claude asking "Start my render?" → Frame Pulse responding "CAUTION: CPU 89%" → User clicking throttle → Success toast]
🤝 Who's Using This
"Frame Pulse caught a thermal spike before our overnight farm render. Saved us 14 hours of redo work."
— Anonymous VFX Supervisor (via DM)
☕ Support the Mission
If this tool saved your render from thermal throttling, prevented a 3AM crash, or helped your AI agent make hardware-aware decisions—consider fueling continued development:
👩🏽💻 Developed by Ida Akiwumi
Lead Product Designer | Creative Technologist | Narrative Strategist
Translating user friction into product opportunities.
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。