# agentscope: LLM Multi-Agent Application Framework and MCP Client

> agentscope is a Python-based MCP Client for building LLM-powered multi-agent applications, offering a drag-and-drop workstation and actor-based distribution. It simplifies complex agent system development with robust fault-tolerance and broad model compatibility.

**Published:** 2026-07-10T16:12:23.678+00:00

**Keywords:** agentscope,mcp-client,multi-agent-llm

# agentscope: Building Distributed LLM Multi-Agent Systems

agentscope is a Python-based MCP Client designed to streamline the creation of LLM-powered multi-agent applications. It provides a framework that simplifies the complexities of distributed agent systems, offering tools like a drag-and-drop workstation and robust fault-tolerance mechanisms.

## Simplifying Multi-Agent Development

The core of agentscope lies in its approach to multi-agent application development. It uses an actor-based distribution model, allowing developers to build distributed systems with a centralized programming paradigm. This abstraction aims to reduce the overhead typically associated with managing distributed components.

Key features supporting this include:
*   **Fruitful Components**: A collection of pre-built elements to accelerate development.
*   **High Robustness**: Custom fault-tolerance controls and retry mechanisms are built-in to enhance application stability.
*   **Comprehensive Documentation**: Resources to guide developers through the framework.
*   **Broad Compatibility**: Support for various model libraries and local deployment options.

## Bridging to Diverse LLMs

agentscope offers extensive compatibility with a range of LLM providers and local deployment methods through its `ModelWrapper`. This allows developers to integrate preferred models without significant refactoring.

Supported third-party APIs include:
*   OpenAI
*   DashScope
*   Gemini
*   ZhipuAI
*   ollama
*   LiteLLM
*   Yi API
*   Anthropic API

For local model deployment, agentscope integrates with libraries such as:
*   ollama
*   Flask
*   Transformers
*   ModelScope
*   FastChat
*   vllm

This flexibility ensures that applications built with agentscope can leverage both cloud-based and self-hosted LLM solutions.

## The AgentScope Workstation and Studio

For developers new to multi-agent systems or looking for a visual approach, agentscope provides two key interfaces:

*   **AgentScope Workstation**: A drag-and-drop programming platform that includes a copilot feature, assisting beginners in constructing agent-based systems.
*   **AgentScope Studio**: An easy-to-use runtime user interface capable of displaying multimodal output, including text, images, audio, and video, on the front end. This provides a visual way to monitor and interact with running agent applications.

Additionally, agentscope includes a **Web Search** tool, allowing agents within the system to retrieve information from the internet.

## Getting Started

agentscope requires Python 3.9 or higher. While a `pip install agentscope` command is available, the project is under active development, and installing from source in editable mode is recommended:

```bash
cd agentscope
pip install -e .
```

Optional dependencies for specific deployment scenarios, such as distribution mode, can be installed as needed.

## References
- [agentscope on GitHub](https://github.com/modelscope/agentscope)
- [Model Context Protocol Documentation](https://modelcontextprotocol.io/introduction)
- [agentscope on model-context-protocol.com](https://model-context-protocol.com/clients/)

## Related Repository

- [llm-multi-agent-application-building-framework](https://model-context-protocol.com/clients/llm-multi-agent-application-building-framework)

**Source:** https://model-context-protocol.com/blog/agentscope-llm-multi-agent-application-framework-and-mcp-client-mcp-client-guide