feat: proof of concept - MCP [not to be merged]

[Henrrypg]

This pull request introduces a proof-of-concept (MVP) implementation of the Model Context Protocol (MCP) for OpenEdx AI Extensions. It adds a minimal working example demonstrating MCP infrastructure, including a FastMCP server with a sample roll_dice tool, a client example, and setup documentation. The changes are focused on validating communication patterns and tool integration, serving as a foundation for future OpenEdx-specific features.

Documentation and Developer Guidance:

• Added a comprehensive README.md explaining the MCP MVP architecture, setup instructions, workflow, and testing steps, specifically for the dice-rolling example.

MCP Server Implementation:

• Introduced server.py implementing a FastMCP server (dice_server) with a sample roll_dice tool that rolls a configurable number of dice.
• Added run_server.py script to launch the MCP server using streamable HTTP transport.

Client Example:

• Added client_example.py, demonstrating how to connect to the MCP server, list available tools, and invoke the roll_dice tool using LiteLLM.

Project Structure:

• Added a package-level docstring in __init__.py to clarify the purpose of the MCP integration for OpenEdx AI Extensions.

[openedx-webhooks]

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[felipemontoya]

best to write this as rst because that is what we use for read the docs

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Additional details and impacted files

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