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About-me

AI & Machine Learning Engineer experienced in developing real-world AI solutions through internships and personal projects. Strong interest in LLMs, intelligent agents, and building scalable AI-powered applications.

Installation
Run this command in your terminal to add the MCP server to Claude Code.
Run in terminal:
Command
claude mcp add adnansaeed-85-about-me

How to use

This repository appears to be a personal README for Adnan Saeed rather than an MCP (Model Context Protocol) server. There is no MCP server definition or runnable server configuration provided in the content. If you intend to deploy an MCP server, you would typically expose one or more servers with a defined command and argument set (for example, a Node.js server at path/to/server.js or a Python/uvx-based service). As is, there are no MCP tools or capabilities to interact with in this repository. If you decide to add an MCP server, you can document its capabilities (e.g., agent orchestration, tool usage, RAG workflows) and present how to invoke it via the MCP manifest you supply here.

How to install

Prerequisites:

  • Decide on the runtime (Node.js, Python/uv, etc.) for your MCP server.
  • Ensure you have the required tooling installed (npm/node, python, uvicorn/uvx, Docker, etc.).

Steps to add an MCP server (example outline):

  1. Create or update your MCP server project with a clear entry point.
  2. Add a manifest documenting the server in this repository, including:
    • mcp_config section describing the server as a named entry under mcpServers
    • how_to_use describing what the server does and available tools
    • how_to_install with exact commands to install and run
  3. If using Node.js, ensure package.json exists and the server script can be started with the path specified in mcp_config.
  4. Test locally and verify MCP protocol compatibility before sharing publicly.

Example commands (depending on your chosen stack):

  • Node.js server (if you add one):
    • npm install
    • node path/to/server.js
  • Python server (uv/uvicorn):
    • python -m your_module
    • uvx run your_module:app
  • Docker-based server:
    • docker build -t your-mcp-server .
    • docker run -i your-mcp-server

Additional notes

Tips:

  • If you maintain multiple MCP servers, list them under distinct names in mcpServers and provide per-server env requirements.
  • Include environment variables in the env object for each server if sensitive values are needed (use placeholders here, e.g., VAR_NAME: "description").
  • Ensure your MCP manifest stays in sync with the actual runtime commands to avoid confusion for users trying to deploy.
  • This README currently does not contain an MCP server configuration; to enable MCP tooling, add a properly formatted mcp_config with concrete server commands.

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