Antonio Montani

About Me

Google Cloud Certified Professional Cloud Architect with expertise in cloud solutions and digital transformation. Based in Paris, France.

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Personal AI Data Source (MCP)

I've deployed a custom Model Context Protocol (MCP) server that allows AI models and agents to access specific details about my professional background using a set of defined tools. This is similar in concept to how ai.jakegaylor.com provides information through an AI interface.

My MCP server, built with Python and FastMCP, parses my professional summary document and exposes tools for targeted information retrieval. It's running on Google Cloud Run.

How it Works & Example Queries:

When connected to an MCP-compatible LLM client (like Claude Desktop or a custom application), the LLM can utilize the tools provided by my server to answer your questions about me. You don't call the tools directly; you ask the LLM a question, and it decides which tool to use.

For example, you could ask the LLM:

• "What is Antonio Montani's professional summary?" (Uses get_summary tool)
• "Tell me about Antonio's experience at Orange Business." (Uses get_professional_experience tool with company_name="Orange Business")
• "What are Antonio's skills in AI Engineering?" (Uses get_skills tool with category="AI Engineering")
• "What is Antonio's educational background?" (Uses get_education tool)
• "Which languages does Antonio speak?" (Uses get_languages tool)
• "Does Antonio have any certifications?" (Uses get_certifications tool)
• "What is Antonio's contact information?" (Uses get_contact_information tool)

Connecting (Example with Claude Desktop):

To use this with an MCP client like Claude Desktop:

1. Open Claude Desktop settings.
2. Navigate to the "MCP Servers" section.
3. Click "Add Server" and choose "Remote Server URL".
4. Enter the server URL: https://antonio-mcp-server-your-unique-hash.a.run.app (Replace with your actual Cloud Run URL after deployment).
5. Give it a name, e.g., "AntonioMontaniProfile_Tools".

The server provides a structured way for AI to access information, promoting more accurate and context-aware responses. Learn more about the Model Context Protocol at modelcontextprotocol.io.