The Streamable MCP Client extends OpenAI Agents to handle live notifications from an MCP server, allowing for real-time progress updates and message streaming during MCP tool execution. It captures every notification chunk instantly and appends it to the agent’s output stream, facilitating seamless, incremental communication and progress visibility.
Added on:
Created by:
May 13 2025
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What is Streamable MCP Client?
This MCP client enables real-time streaming of MCP notifications and tool outputs, providing immediate feedback on ongoing tasks. It listens to notifications from an MCP server, surfaces each message in real time, and integrates them into the agent's response flow. The client is designed for applications requiring live updates, such as progress indicators or incremental messaging, by merging notification streams with the model’s output. It supports extension and customization, patches the SDK for step-by-step control, and integrates with reference MCP servers for demonstration of long-running processes, ensuring developers can build interactive and responsive AI-powered tools.
Who will use Streamable MCP Client?
- AI developers
- Chatbot integrators
- Realtime monitoring system builders
- Research engineers
- Automation tool creators
How to use the Streamable MCP Client?
- Step 1: Set up an MCP server and ensure it is running.
- Step 2: Clone and install the streamable-mcp-client repository.
- Step 3: Configure your application to connect to the MCP server and select client mode.
- Step 4: Initiate a streamed run using the agent's run_streamed() method.
- Step 5: Observe real-time notification and message streaming in your UI or console.
Streamable MCP Client's Core Features & Benefits
The Core Features
- Surface and stream MCP notifications during active tool runs
- Merge notification chunks into ongoing responses in real time
- Patch and extend OpenAI SDK for step-by-step execution control
- Support reference MCP servers for demos and testing
- Multiplex agent events and notifications seamlessly
The Benefits
- Provides real-time visibility into long-running tasks
- Enables incremental output display for better user experience
- Enhances integration flexibility with MCP servers and tools
- Supports customization for advanced notification handling
Streamable MCP Client's Main Use Cases & Applications
- Building interactive AI assistants with live updates
- Monitoring long-running operations or data processing tasks
- Real-time progress tracking in automation workflows
- Developing live notification systems for MCP-based tools
FAQs of Streamable MCP Client
Developer
- josephbharrison