• Design, develop, and maintain MCP servers that expose external tools and capabilities to AI assistants. • Implement specific MCP tools (functions) for reading files, managing issues, interacting with databases, or triggering complex workflows. • Define and structure resources, schemas, and prompts accessible to AI agents. • Ensure security and access control for the MCP server, limiting which tools and data agents can execute or access. • Manage API integrations and external data sources used by MCP tools. • Use JSON Schema or similar standards to document and validate tool definitions. • Integrate MCP Server tools with Azure AI Foundry agents, enabling AI agents to perform actions such as data querying, workflow automation, and API interaction. • Collaborate with product managers and front-end teams to integrate AI capabilities into user-facing platforms (e.g., Microsoft Copilot, VS Code extensions, or web portals). • Utilize Azure Functions, Azure Logic Apps, and Azure Cognitive Services to connect MCP-based AI workflows to enterprise systems. • Develop and manage tools that interface with Azure resources (e.g., Azure Storage, Azure SQL, Azure Compute Services) through the MCP Server. • Enable AI agents to securely manage, retrieve, and utilize Azure resources. • Apply best practices in cloud security, authentication, and API permissions management. • Conduct comprehensive testing and debugging of MCP tools and Azure integrations. • Create detailed documentation for MCP tools, including usage examples, API specifications, and integration guides. • Ensure scalability, performance, and reliability of MCP and AI Foundry deployments. • Partner with AI engineers, cloud architects, and data scientists to align tool development with strategic goals. • Present technical solutions and architectural decisions to stakeholders in clear, actionable terms. • Contribute to the AI governance framework, ensuring responsible AI tool design and usage.