Distri is a modular AI agent framework written in Rust, enabling users to create, publish, and compose agents using YAML or rust-script. It leverages MCP (Multi-Agent Communication Protocol) for structured agent communication, capability sharing, and task collaboration. Suitable for developers building AI ecosystems, Distri facilitates reliable, high-performance agent interactions and easy integration of new functionalities.
Added on:
Created by:
Apr 01 2025
Distri is a modular AI agent framework written in Rust, enabling users to create, publish, and compose agents using YAML or rust-script. It leverages MCP (Multi-Agent Communication Protocol) for structured agent communication, capability sharing, and task collaboration. Suitable for developers building AI ecosystems, Distri facilitates reliable, high-performance agent interactions and easy integration of new functionalities.
Added on:
Created by:
Apr 01 2025
distrihub
Featured
What is Distri?
Distri is a comprehensive framework designed for building and orchestrating AI agents with a focus on modularity and scalability. Built in Rust, it allows developers to create agents that can communicate via the standardized MCP (Multi-Agent Communication Protocol), share capabilities, and collaborate on tasks. Users can configure agents through YAML files or advanced Rust scripts, making it accessible for different expertise levels. Distri also supports publishing agents as reusable MCP-compatible tools, fostering an ecosystem of AI components. It is ideal for developers seeking robust, high-performance multi-agent systems for automation, data processing, or AI integrations in diverse environments.
Who will use Distri?
- AI researchers
- AI developers
- System integrators
- DevOps engineers
- Organizations deploying multi-agent systems
How to use the Distri?
- Step1: Install Distri via Cargo or Docker
- Step2: Configure agents using YAML or Rust scripts
- Step3: Run agents with the `distri run` command and your configuration
- Step4: Use `distri list` to view and manage agents
- Step5: Use MCP tools for communication and capability sharing among agents
Distri's Core Features & Benefits
The Core Features
- Agent creation and configuration via YAML and Rust
- Standardized MCP communication protocol
- Capability sharing and publishing
- Agent composition and orchestration
- Support for modular and scalable agent systems
The Benefits
- High-performance execution with Rust
- Flexible configuration options
- Interoperability through MCP standard
- Ecosystem of reusable AI components
- Ease of integration and deployment
Distri's Main Use Cases & Applications
- Developing multi-agent AI ecosystems
- Automating workflows with AI agents
- Building scalable AI assistant systems
- Integration of diverse AI tools and capabilities
- Collaborative AI research projects
FAQs of Distri
Developer
- distrihub
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