Azure OpenAI

by kimtth
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Python
MIT License
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MCP Server & Client implementation for using Azure OpenAI

  • A minimal server/client application implementation utilizing the Model Context Protocol (MCP) and Azure OpenAI.
    1. The MCP server is built with FastMCP.
    2. Playwright is an an open source, end to end testing framework by Microsoft for testing your modern web applications.
    3. The MCP response about tools will be converted to the OpenAI function calling format.
    4. The bridge that converts the MCP server response to the OpenAI function calling format customises the MCP-LLM Bridge implementation.
    5. To ensure a stable connection, the server object is passed directly into the bridge.

Model Context Protocol (MCP)

Model Context Protocol (MCP) MCP (Model Context Protocol) is an open protocol that enables secure, controlled interactions between AI applications and local or remote resources.

Official Repositories

Community Resources

  • FastMCP: The fast, Pythonic way to build MCP servers.
  • Chat MCP: MCP client
  • MCP-LLM Bridge: MCP implementation that enables communication between MCP servers and OpenAI-compatible LLMs

MCP Playwright

Configuration

During the development phase in December 2024, the Python project should be initiated with 'uv'. Other dependency management libraries, such as 'pip' and 'poetry', are not yet fully supported by the MCP CLI.

  1. Rename .env.template to .env, then fill in the values in .env for Azure OpenAI:
    AZURE_OPEN_AI_ENDPOINT= AZURE_OPEN_AI_API_KEY= AZURE_OPEN_AI_DEPLOYMENT_MODEL= AZURE_OPEN_AI_API_VERSION=
  2. Execute chatgui.py
    • The sample screen shows the client launching a browser to navigate to the URL.
    <img alt="chatgui" src="doc/chatgui_gpt_generate.png" width="300"/>

w.r.t. 'stdio'

stdio is a transport layer (raw data flow), while JSON-RPC is an application protocol (structured communication). They are distinct but often used interchangeably, e.g., "JSON-RPC over stdio" in protocols.

Tool description

@self.mcp.tool() async def playwright_navigate(url: str, timeout=30000, wait_until="load"): """Navigate to a URL.""" -> This comment provides a description, which may be used in a mechanism similar to function calling in LLMs. # Output Tool(name='playwright_navigate', description='Navigate to a URL.', inputSchema={'properties': {'url': {'title': 'Url', 'type': 'string'}, 'timeout': {'default': 30000, 'title': 'timeout', 'type': 'string'}

uv

pip install uv
uv run: Run a script. uv venv: Create a new virtual environment. By default, '.venv'. uv add: Add a dependency to a script uv remove: Remove a dependency from a script uv sync: Sync (Install) the project's dependencies with the environment.

Tip

  • taskkill command for python.exe
taskkill /IM python.exe /F
  • Visual Code: Python Debugger: Debugging with launch.json will start the debugger using the configuration from .vscode/launch.json.
<!-- ### Sample query Navigate to website http://eaapp.somee.com and click the login link. In the login page, enter the username and password as "admin" and "password" respectively and perform login. Then click the Employee List page and click "Create New" button and enter realistic employee details to create for Name, Salary, DurationWorked, Select dropdown for Grade as CLevel and Email. -->
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security - not tested
A
license - permissive license
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quality - not tested

A minimal server/client application implementation utilizing the Model Context Protocol (MCP) and Azure OpenAI.

  1. Model Context Protocol (MCP)
    1. Official Repositories
      1. Community Resources
        1. Related Projects
          1. MCP Playwright
            1. Configuration
              1. w.r.t. 'stdio'
                1. Tool description
                  1. uv
                    1. Tip