AI Bridge

A hands-on curriculum for building an application that talks to a generative AI model, and extending it into an MCP server an AI agent can use.

• 📖 The curriculum — 9 modules, start to finish
• 💻 Plant Service — the finished, tested reference implementation the curriculum builds

Reading it

You can read the curriculum directly on GitHub (the links above), or as a built site — this repo is set up to publish one automatically with MkDocs + Material.

Publishing to GitHub Pages

1. Push this repo to GitHub.
2. The deploy-docs.yml workflow runs on every push to main, building the site and pushing it to a gh-pages branch.
3. After the first run, go to the repo's Settings → Pages, and under Build and deployment → Source, choose Deploy from a branch, then select the gh-pages branch and / (root) folder.
4. The site will be live at https://<your-username>.github.io/<repo-name>/.

Building it locally

python3 -m venv env
source env/bin/activate
pip install -r requirements-docs.txt

mkdocs serve   # live preview at http://localhost:8000
# or
mkdocs build   # outputs the static site to site/

Repo layout

curriculum/       the 9 markdown modules (also the MkDocs docs_dir)
curriculum/plant-service   a symlink to ../plant-service — lets the
                           curriculum's relative links to code samples
                           resolve on the built site, not just on GitHub
plant-service/     the reference app itself (source of truth; edit here,
                    not through the symlink)
mkdocs.yml         site config
requirements-docs.txt   dependencies for building/serving the site