modelscope-agent
VerifiedLightweight open-source framework for building agents with autonomous exploration and tool use.
What is modelscope-agent?
MS-Agent is a Python-based framework that enables developers to build agents capable of autonomous exploration and task execution. It integrates support for general-purpose tool calling via MCP along with specialized capabilities like context compression and knowledge retrieval over local files.
Agents operate through configurable components that manage conversation history, prune outputs when needed, and incorporate multimodal data such as images or video. The system scales from simple chat interactions to full deep-research pipelines while remaining easy to customize.
It targets researchers and developers who need an extensible platform for prototyping agent behaviors without heavy infrastructure overhead.
Capabilities
What you can build with modelscope-agent
Deep Research
Run autonomous exploration agents that retrieve information, summarize findings, and produce structured reports using integrated search tools.
Code Generation
Generate and iterate on code artifacts through agent interactions that support complex programming tasks and real-time feedback.
Short Video Creation
Produce short videos around five minutes in length by leveraging agent skills for content planning and rendering workflows.
Install modelscope-agent
pip install ms-agent# For the basic functionalities
pip install ms-agent
# For the deep research functionalities
pip install 'ms-agent[research]'- 1Install the package with pip install ms-agent.
- 2Review the configuration documentation to set up MCP tools and model endpoints.
- 3Launch the WebUI to interact with agents via WebSocket in real time.
- 4Load an example project such as Agentic Insight v2 for deep research.
- 5Extend the agent by implementing custom skills following the supported protocol.
modelscope-agent: pros & cons
Pros
- +Lightweight design with straightforward extension points
- +Built-in WebUI and real-time communication support
- +Strong focus on autonomous research and context management
- +Multimodal input handling and local knowledge search
Cons
- –Requires Python 3.10 or higher
- –Advanced features like deep research may need additional model access
- –Documentation split between English and Chinese versions
Frequently asked questions
It serves as a lightweight framework for developing agents that can explore tasks autonomously and call tools through the MCP protocol.
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