mcp-agent vs Qwen-Agent
Python frameworks for tool-using LLM agents compared
mcp-agent and Qwen-Agent are Python frameworks for building LLM applications that use tools, including tools exposed through MCP servers. mcp-agent emphasizes composable workflows and optional Temporal durability, while Qwen-Agent focuses on Qwen-based assistants with features and examples for function calling, documents, and code execution.
mcp-agent: Build Agents with Model Context Protocol
A Python framework for building LLM agents around Model Context Protocol servers and composable workflow patterns. It suits developers who need MCP integrations, multi-agent workflows, or durable execution with Temporal.
Qwen-Agent: Build Tool-Using LLM Applications
Qwen-Agent is a Python framework for building Qwen-based assistants that can call tools, plan tasks, and work with documents. Use it to prototype or deploy agent applications when you need integrations such as MCP, code execution, or retrieval-augmented generation.
| mcp-agent | Qwen-Agent | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Stars | 8.6k | 17.1k |
| Forks | 893 | 1.7k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- mcp-agent offers reusable workflow patterns such as routers and orchestrator-workers; Qwen-Agent centers on agent abstractions and built-in assistants.
- mcp-agent supports asyncio or Temporal execution, with Temporal workflows able to pause, resume, and retry; Qwen-Agent's described capabilities include function calling, RAG examples, and a Docker-based code interpreter.
- mcp-agent can expose applications and agents as MCP servers; Qwen-Agent describes connecting agents to configured MCP servers.
- Qwen-Agent includes examples for browser assistance and code interpretation, plus an optional Gradio GUI; mcp-agent provides a CLI for scaffolding and deployment.
- Both projects use Python and Apache-2.0 licensing. The supplied project data lists 8.6k stars for mcp-agent and 17.1k for Qwen-Agent.
Choose mcp-agent if you…
- need composable agent workflows such as parallel map-reduce or evaluator-optimizer patterns.
- want optional Temporal-backed pause, resume, and retry behavior for long-running workflows.
- need to expose an application or agent as an MCP server.
Choose Qwen-Agent if you…
- want to build applications around Qwen models with function calling and custom tools.
- need document question-answering examples using retrieval-augmented generation.
- want examples or optional components for browser assistance, a Gradio GUI, or Docker-based code execution.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.