fast-agent and jaf-py
These tools appear to be **competitors**, as both `evalstate/fast-agent` and `xynehq/jaf-py` are designed as agent frameworks offering "MCP" support for building AI systems, suggesting they aim to fulfill similar core functionalities.
About fast-agent
evalstate/fast-agent
Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP Support
This tool helps developers and AI practitioners quickly build, evaluate, and deploy AI agents that interact with large language models (LLMs). It takes your instructions and configurations, allowing you to create agents that can code, answer questions, or automate tasks. The output is a functional AI agent or workflow ready to be integrated into applications or used interactively.
About jaf-py
xynehq/jaf-py
Functional Python agent framework with MCP support, enterprise security, immutable state, and production-ready observability for building scalable AI systems.
This is a Python framework designed for software engineers building advanced AI agent systems. It helps create robust, scalable, and secure AI applications by providing tools for agent orchestration, enterprise security features, and built-in observability. Engineers can feed in complex instructions and tools to develop AI agents that can interact, make decisions, and automate tasks.
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