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Django MCP Streamable Http Server View
Example of an MCP protocol streaming HTTP server view implemented based on the Django framework
rating : 2 points
downloads : 6
What is the Django MCP Streamable HTTP Server?
This is a Django server that implements the Model Context Protocol (MCP) specification, allowing clients to interact with AI models via the HTTP protocol. The server supports streaming responses, making it suitable for handling long-running model inference tasks.How to use the Django MCP Streamable HTTP Server?
Simply copy the provided views.py file into your Django application and configure the corresponding URL routes to quickly set up a server endpoint that complies with the MCP specification.Use cases
Suitable for scenarios where AI models need to be served via the standard HTTP protocol, especially AI applications that require support for long-running tasks and streaming responses.Main features
MCP specification complianceFully implemented in accordance with the Model Context Protocol (MCP) 2025 - 03 - 26 specification
Streaming HTTP responseSupports chunked transfer encoding for real - time streaming responses
Seamless Django integrationImplemented as a standard Django view, easy to integrate with existing Django projects
Advantages and limitations
Advantages
Rapid deployment: Copy a single file to get full MCP server functionality
Standardization: Follows the MCP specification to ensure compatibility with other MCP clients
Flexibility: Based on the Django framework, easy to extend and customize
Limitations
Only supports the HTTP protocol and does not support other transport protocols in the MCP specification
Requires a Django environment and is not suitable for lightweight deployment scenarios
The implementation of streaming responses depends on Django's StreamingHttpResponse
How to use
Install dependencies
Ensure that the Django framework and necessary Python dependencies are installed
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Add view file
Copy the provided views.py file into your Django application
Configure URL routes
Add route configuration for the MCP endpoint in urls.py
Start the server
Run the Django development server or deploy it to a production environment
Usage examples
Text generation taskUse the MCP server to handle long text generation tasks and obtain the generated results in real - time
Image processing taskProcess image recognition tasks through the MCP server and return the recognition results in stages
Frequently Asked Questions
Which models does the MCP server support?
How to handle large file uploads?
How to extend the server functionality?
Related resources
MCP specification document
Official specification document of the Model Context Protocol
GitHub repository
Project source code and examples
Django documentation
Official documentation of the Django framework
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