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Table of contents

• Why this exists
• Demo
• Tools exposed
• Quickstart
• Connect to Claude Desktop
• Stack
• Testing & CI
• Project structure
• Roadmap
• License
• Author

Why this exists

Most AI-developer portfolios are a list of links. This is a working MCP server — the same protocol agentic products use to connect to tools — built around my own portfolio. It's both a real implementation of the spec and an answer to "show me you've actually built with MCP," not just talked about it.

Demo

🎥 Full video walkthrough

https://github.com/user-attachments/assets/4c1b844a-087f-48a6-b156-bdef27282acc

Setup → tool calls → live answers, end to end.

Tools exposed

Quickstart

Option A — install from PyPI (fastest):

pip install portfolio-mcp-server

Option B — clone and run from source (for local edits/testing):

git clone https://github.com/ayush-s-tomar/portfolio-mcp-server.git
cd portfolio-mcp-server

python -m venv venv
source venv/bin/activate        # Windows: venv\Scripts\activate

pip install -r requirements.txt

Test it interactively with the MCP Inspector before wiring it into a client:

mcp dev server.py

This opens a browser UI where you can call each tool manually and inspect raw request/response payloads.

Connect to Claude Desktop

Open your Claude Desktop config file:

If the file already has an mcpServers key with other servers in it, add the "portfolio" entry inside the existing object rather than overwriting the file.

If you installed via PyPI (Option A above):

{
  "mcpServers": {
    "portfolio": {
      "command": "portfolio-mcp-server"
    }
  }
}

If you're running from a cloned source checkout (Option B above): use the absolute path to server.py on your machine:

{
  "mcpServers": {
    "portfolio": {
      "command": "python",
      "args": ["/absolute/path/to/portfolio-mcp-server/server.py"]
    }
  }
}

Restart Claude Desktop, then ask it something like:

"What projects has Ayush built with FastAPI?"

Claude will call search_projects_by_stack and answer from the live data.

Stack

• Python 3.10+
• MCP Python SDK (FastMCP)
• stdio transport
• Packaged for PyPI and registered on the official MCP server registry (io.github.ayush-s-tomar/portfolio-mcp-server)

Testing & CI

Every push and pull request runs through GitHub Actions:

• Lint — ruff check .
• Type check — mypy server.py
• Smoke test — spins up the server and calls each of the 5 tools over stdio to confirm they return valid, schema-matching JSON

See .github/workflows/ci.yml. Run the same checks locally before opening a PR:

pip install -r requirements-dev.txt
ruff check .
mypy server.py
pytest

Project structure

portfolio-mcp-server/ ├── server.py # FastMCP server + tool definitions ├── data/ │ └── projects.json # Project data the tools read from ├── tests/ │ └── test_tools.py # Smoke tests for each tool ├── requirements.txt ├── requirements-dev.txt ├── pyproject.toml # PyPI packaging config ├── server.json # MCP registry manifest └── .github/workflows/ci.yml

Roadmap

• Publish to PyPI as an installable package
• Publish to the official MCP server registry
• search_projects_by_stack — support matching on multiple technologies at once
• Add an HTTP/SSE transport option alongside stdio for remote clients
• Cache resume/project data with a lightweight refresh endpoint instead of static JSON

License

Released under the MIT License.

Author

Ayush Tomar — GitHub

If this was useful as a reference for building your own MCP server, a ⭐ on the repo is appreciated.

mcp-name: io.github.ayush-s-tomar/portfolio-mcp-server