9ba615c8ee
Template for building hosted MCP servers over a product's public
documentation. Distilled from one production build; everything
product-specific has been factored out.
Contents:
- PLAN.md — comprehensive build guide. 13 phases from project
skeleton through weekly_digest. Includes the gotchas
("fetch-depth: 0 always", reranker per-pair token limit,
Cloudflare body cap, dash-not-bash on Gitea runners), the
decisions worth carrying forward, and a per-product
customization checklist.
- CLAUDE.md — guidance for Claude Code working in a clone of this
template. Phase identification table, conventions (env-gating +
operator confirmation for side-effecting tools, defensive
fallback for retrieval components), common commands.
- README.md — quick-start summary.
Scaffolded code (all signature-stable, with NotImplementedError
stubs where phase-specific work is required):
docs_mcp/server.py FastMCP server, stateless_http=True, with
search_docs / get_page / list_versions
baseline tools and commented stubs for the
rest of the phase set.
docs_mcp/usage.py TimedCall telemetry, JSONL, daily rotation,
90-day retention. Reusable as-is.
rag/embeddings.py Ollama embedder (nomic-embed-text default),
load-balanced across N URLs. Reusable.
rag/chunk.py Paragraph-aware chunker with synthetic
chunk 0. Per-product tunable.
rag/index.py Chroma + BM25 builder. --rebuild and
--bm25-only flags.
rag/bm25.py SQLite FTS5 lexical index. Reusable.
scrape/changelog.py --cached / --ref / --json / --history-out.
Reusable.
scrape/README.md What you write per-product.
eval/queries.jsonl.example
Curate ~25 hand-labeled queries here.
eval/retrievers.py Retriever protocol + stub classes.
eval/run_eval.py MRR / Recall@K / nDCG@K harness skeleton.
scripts/usage_report.py
Standalone log analyzer; the
FOLLOW-UP CHECKS pattern noted in the
module docstring.
scripts/registry_gc.py
Gitea container registry cleanup. Reusable.
Deployment + CI:
Dockerfile Python 3.12-slim; COPY corpus + chroma
+ bm25 last for cache efficiency.
deploy/docker-compose.yml MCP + reranker sidecar + Watchtower.
Templated with <placeholders>.
.gitea/workflows/refresh.yml Weekly cron + manual dispatch.
fetch-depth: 0, retry-on-race,
three-tag image scheme.
.gitea/workflows/image-only.yml Code-only ship cycle, ~18min.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
scrape/
Product-specific. You implement this for each product. The template gives you the contract; the extraction logic depends on the upstream doc portal.
See PLAN.md Phase 1 for the corpus layout the rest of the pipeline
expects.
What you write
At minimum, two scripts:
scrape/bundles.py
Discovers the upstream portal's bundle catalog and writes
bundles.json at the repo root. One entry per bundle (versioned doc
set) with the schema in PLAN.md.
python -m scrape.bundles
scrape/runner.py
Scrapes the pages of each bundle (or a single bundle with --bundle <slug>). Writes:
corpus/<bundle_id>/<page_id>.md— extracted markdown bodycorpus/<bundle_id>/<page_id>.json— per-page metadata sidecar
python -m scrape.runner --all --force --concurrency 6
python -m scrape.runner --bundle Admin.VC.HTML.10.9
Tips
- Sniff before you scrape. Almost every modern doc portal is an SPA that calls a backend API. Open the browser's Network tab, click around, find the underlying JSON. Scraping the API is 10× cheaper and 100× more reliable than scraping the rendered HTML.
- Idempotent re-scrapes. Without
--force, the runner should skip pages already on disk so a resume doesn't have to re-fetch everything. With--force, re-fetch every page — that's the weekly cron mode that catches edits. - Respect the portal. Backoff on 429s. Set a recognizable user-agent so the portal owner can identify you if they want to.
- Whitespace normalize. Markdown that round-trips through HTML often has extra blank lines. Normalize to a single blank between paragraphs so diffs are clean (the changelog summary and digest tools care about line counts).
What's already reusable
scrape/changelog.py is fully product-agnostic and ready to use
as-is. It walks git diff --name-status output to produce a
structured summary, and walks git log for the digest history
(Phase 13).