Agents Orchestra
byaviz85
0Orchestrates agent workflows using state-based transitions and the Model Context Protocol (MCP).
About
This Python implementation offers a state-based agent orchestration system leveraging the Model Context Protocol (MCP) to streamline LLM interactions. It allows for the creation of resources, tools, and prompts, defining clear agent states like planning, researching, and executing tasks. With this tool, you can customize agent behavior, add new states, define custom tools, and integrate with Claude for Desktop to create sophisticated, context-aware AI workflows.
Key Features
- State-based agent orchestration
- 0 GitHub stars
- Integration with Claude for Desktop
- Model Context Protocol (MCP) integration
- Tool creation with the @mcp.tool() decorator
- Customizable agent states and transitions
Use Cases
- Building complex AI workflows with stateful agents
- Providing context for LLMs in a standardized way
- Automating tasks using predefined plans and actions