📦

agent-mcp-lab

by WaveSpeedAI/agent-mcp-lab

0 views

No description available

pythonapiintegrationAPI Integration

MCP Agent Ecosystem: Revolutionizing Development with One-Click Multimodal Activation

Empowering global developers to seamlessly integrate and activate advanced multimodal capabilities in AI agents through the WavespeedAI MCP platform.

What is the MCP Agent Ecosystem?

The MCP Agent Ecosystem provides a unified framework for developers to connect, enhance, and deploy AI agents with powerful multimodal capabilities. By leveraging WavespeedAI's MCP (Multimodal Communication Protocol) Server, developers can:

  • Instantly activate multimodal capabilities in existing AI agents
  • Seamlessly integrate vision, voice, and text processing in real-time
  • Accelerate development with standardized protocols and pre-built components
  • Scale globally with enterprise-grade infrastructure support

This repository contains tutorials, examples, and integration guides for connecting various AI agents to the WavespeedAI MCP Server ecosystem.

MCP Server: Multimodal Capabilities

WavespeedMCP Server is our official implementation of the Model Control Protocol (MCP) server for WaveSpeed AI services. It provides a standardized interface for accessing advanced multimodal capabilities through the MCP protocol.

Key Features

  • Advanced Image Generation: Create high-quality images from text prompts with support for image-to-image generation, inpainting, and LoRA models
  • Dynamic Video Generation: Transform static images into videos with customizable motion parameters
  • Optimized Performance: Enhanced API polling with intelligent retry logic and detailed progress tracking
  • Flexible Resource Handling: Support for URL, Base64, and local file output modes
  • Comprehensive Error Handling: Specialized exception hierarchy for precise error identification and recovery

The MCP Server follows a clean, modular architecture with components for server implementation, API client optimization, resource handling, and error management. It can be easily configured through environment variables, command-line arguments, or configuration files.

List of AI Agents

NameGitHubintroRemarkIntegration Guide
Cursorgetcursor/cursorThe AI Code Editor - A powerful coding assistant built for programming with AI.Features advanced code generation, editing, and explanation capabilities with support for multiple AI models. Offers deep codebase understanding and project-wide context awareness.
WindsurfWindsurfA next-generation AI IDE built to keep developers in the flow.Features Cascade, an agentic chatbot that can collaborate with developers, with advanced context awareness and terminal integration. Supports MCP for extended agent capabilities.Windsurf Integration Guide
TraeTrae-AI/TraeA powerful AI IDE with seamless MCP integration for rapid multimodal Agent capabilities.Features one-click activation of multimodal functions through WaveSpeed MCP, enabling Agents to generate and edit images/videos efficiently. Supports fast integration with minimal configuration for immediate multimodal capabilities.Trae Integration Guide
AIpyknownsec/aipyappAI-Powered Python & Python-Powered AI (Python-Use) - A new paradigm for AI agents.Provides the entire Python execution environment to LLMs, allowing them to freely use all Python features without predefined tool interfaces. Supports both task mode and Python mode.AIpy Integration Guide
Local Manus11cafe/local-manusAI Marketing Agent & Copilot - A local alternative for Manus.Features AI marketing content copilot, 1-click cross-posting to multiple platforms, AI "ReplyGuy" for automatic engagement, and upcoming image & video enhancements. Supports both cloud AI models and local models via Ollama.
Jaaz11cafe/jaazAI Design Agent - A local alternative for Lovart.Features AI designer agent for image generation and editing, canvas and storyboard creation, and support for various models including Ollama, Stable Diffusion, and Flux. Enables object removal, style transfer, and consistent character generation through chat.

Install

No configuration available
For more configuration details, refer to the content on the left

Related

Related projects feature coming soon

Will recommend related projects based on sub-categories