initial: docs-mcp-template — build guide + scaffolded server
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>
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# scrape/
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Product-specific. **You implement this for each product.** The
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template gives you the contract; the extraction logic depends on
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the upstream doc portal.
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See `PLAN.md` Phase 1 for the corpus layout the rest of the pipeline
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expects.
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## What you write
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At minimum, two scripts:
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### `scrape/bundles.py`
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Discovers the upstream portal's bundle catalog and writes
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`bundles.json` at the repo root. One entry per bundle (versioned doc
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set) with the schema in PLAN.md.
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```bash
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python -m scrape.bundles
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```
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### `scrape/runner.py`
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Scrapes the pages of each bundle (or a single bundle with `--bundle
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<slug>`). Writes:
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- `corpus/<bundle_id>/<page_id>.md` — extracted markdown body
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- `corpus/<bundle_id>/<page_id>.json` — per-page metadata sidecar
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```bash
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python -m scrape.runner --all --force --concurrency 6
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python -m scrape.runner --bundle Admin.VC.HTML.10.9
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```
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## Tips
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- **Sniff before you scrape.** Almost every modern doc portal is an
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SPA that calls a backend API. Open the browser's Network tab,
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click around, find the underlying JSON. Scraping the API is 10×
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cheaper and 100× more reliable than scraping the rendered HTML.
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- **Idempotent re-scrapes.** Without `--force`, the runner should
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skip pages already on disk so a resume doesn't have to re-fetch
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everything. With `--force`, re-fetch every page — that's the
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weekly cron mode that catches edits.
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- **Respect the portal.** Backoff on 429s. Set a recognizable
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user-agent so the portal owner can identify you if they want to.
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- **Whitespace normalize.** Markdown that round-trips through HTML
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often has extra blank lines. Normalize to a single blank between
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paragraphs so diffs are clean (the changelog summary and digest
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tools care about line counts).
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## What's already reusable
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`scrape/changelog.py` is fully product-agnostic and ready to use
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as-is. It walks `git diff --name-status` output to produce a
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structured summary, and walks `git log` for the digest history
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(Phase 13).
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