mcp 2.0.0 removed `mcp.server.fastmcp`. This repo was pinned to <2
(6723829) to stop a rebuild from crash-looping the container the way
seed-mcp (2026-09-01) and zerto-docs (2026-08-11) did. This lifts the
pin by doing the port — the same mechanical change as
justin/seed-mcp#23 and justin/morpheus-docs#10.
- import: FastMCP -> MCPServer, plus TransportSecuritySettings
- constructor takes no transport options: MCPServer(f"{PRODUCT_NAME}-docs")
- host/port/stateless_http/transport_security are run() kwargs;
`mcp.settings` no longer exists
- requirement becomes plain `mcp>=2,<3` (2.x has no [fastmcp] extra)
@mcp.tool() decorators and all handler signatures are unchanged.
CI now smokes `import docs_mcp.server` twice in both workflows — once
after pip install, once inside the built image — so a green build can
never ship a non-importing container again.
Verified on python:3.12-slim (matches the image):
- tools/list dumped in wire format is BYTE-FOR-BYTE IDENTICAL between
mcp 1.30.0 and 2.2.0, all 10 tools
- streamable-http boots; initialize returns HTTP 200, both from
localhost and with a container-DNS `Host: hvm-docs-mcp:8000` header
(passing host= to run() keeps DNS-rebinding protection off)
- no mcp-session-id response header, i.e. stateless_http is in effect
- stdio boots; initialize + tools/list return 10 tools
- production image builds and imports under mcp 2.2.0; httpx 0.28.1 and
httpx2 2.12.0 coexist as expected
Retrieval is untouched, so no eval numbers are included.
Closes #12
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01QBx2P1VhKQEzJWoZ96QcnH
253 lines
11 KiB
Markdown
253 lines
11 KiB
Markdown
# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when
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working with code in this repository.
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## Purpose
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This is a **template** for building an MCP server over a product's
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public documentation. When you (Claude) are working in a clone of this
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repo, you are helping the user implement one specific product's docs
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MCP — not editing the template itself.
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**Read `PLAN.md` first.** It's the canonical build guide and lays out
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13 phases. Most user requests will be "implement Phase N" or "we hit
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a bug in Phase N." Identify the phase before doing anything else.
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## Working with this template
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### Identifying the current phase
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When the user clones this template and starts working, figure out
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which phase they're on by inspecting:
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| Signal | Likely phase |
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|---|---|
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| `corpus/` doesn't exist | Phase 1 (scraper) — they need to build it before anything else works |
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| `corpus/` exists, `chroma/` doesn't | Phase 2 (indexing) |
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| Indexes exist, only `search_docs` / `get_page` / `list_versions` implemented | Phase 3 (server skeleton done; next: Dockerfile + CI) |
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| No `Dockerfile` or `.gitea/workflows/` updated | Phase 4–5 |
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| `RERANK_URL` env unset in compose | Phase 6 not done |
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| `HYBRID_SEARCH` env unset, no `rag/bm25.py` content | Phase 8 not done |
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| No `eval/results/` directory | Phase 7 not done |
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| `find_doc_inconsistencies` / `submit_doc_bug` are commented-out stubs in `docs_mcp/server.py` | Phase 12 |
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| No `corpus/.digest/` produced by CI | Phase 13 |
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When in doubt, ask the user: *"Which phase from PLAN.md are we
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working on?"*
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### The scaffolded server has stubs
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`docs_mcp/server.py` ships with three working tools (`search_docs`,
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`get_page`, `list_versions`) and signature-only stubs for the
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phase-specific tools. The stubs `raise NotImplementedError` with a
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phase hint in the docstring. When implementing a phase, you'll be
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filling these bodies in — DO NOT change the signatures unless the
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user has a specific reason. Signatures are the public contract
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between the MCP and its clients (Claude Desktop, Claude Code,
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Cursor, etc.).
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## Layout
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```
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.
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├── PLAN.md # Read first. Phase-by-phase build guide.
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├── README.md # Quick-start summary.
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├── CLAUDE.md # This file.
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├── requirements.txt
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├── Dockerfile
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├── deploy/docker-compose.yml
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├── .gitea/workflows/
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│ ├── refresh.yml # Weekly cron: scrape + index + image
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│ └── image-only.yml # On-demand: code-only ship cycle
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├── scrape/ # Phase 1 — product-specific scraper here
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│ └── changelog.py # Reusable: --json, --history-out
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├── rag/ # Phase 2/8 — indexing
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│ ├── embeddings.py # Ollama embedder (swappable)
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│ ├── chunk.py # Page → chunks (adjust per page format)
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│ ├── index.py # Builds Chroma + BM25
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│ └── bm25.py # SQLite FTS5 lexical index
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├── docs_mcp/ # Phase 3+ — MCP server
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│ ├── server.py # MCPServer + tool definitions
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│ └── usage.py # TimedCall telemetry
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├── eval/ # Phase 7 — golden-query harness
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│ ├── queries.jsonl.example
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│ ├── retrievers.py
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│ └── run_eval.py
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├── scripts/ # Standalone ops scripts
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│ ├── usage_report.py
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│ └── registry_gc.py
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└── deploy/
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└── docker-compose.yml
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```
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## Conventions
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### Tool docstrings are user interface
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The text in `@mcp.tool()` docstrings is what the LLM sees and uses to
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decide whether to call the tool. Treat it like a button label.
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*"Use when..."*, *"Call proactively whenever..."* phrasings work
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well. Don't bury the headline in implementation notes.
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### Side-effecting tools must be env-gated AND operator-confirmed
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Any tool that POSTs to an external service (submit_doc_bug being the
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canonical example):
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1. Must check an env flag at call time and return a "disabled,
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manual fallback at <URL>" message if unset.
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2. Must have a loud docstring requiring per-call operator
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confirmation in the LLM conversation flow (the LLM drafts, shows
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the operator the exact payload, asks yes/no, only then calls).
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3. Must do upfront validation (URL allowlist, content length, etc.)
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so the LLM gets a clean error instead of a wire-level failure.
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Match the `submit_doc_bug` patterns documented in PLAN.md Phase 12.
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### Defensive fallback for retrieval components
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The reranker, BM25 index, and any external dependency must fail
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gracefully:
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- Catch the specific exception type
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- Log a warning with enough info to debug
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- Fall back to a working baseline (dense-only, no reranker, etc.)
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- Never block a search_docs call on a single failure
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The user's MCP is in front of real people; partial degradation
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beats a 500.
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### Verify retrieval changes with the eval harness
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Any change that touches retrieval (new embedder, chunker tweak,
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reranker model, filter shape) ships with eval numbers in the commit
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message. Don't ship retrieval changes on vibes. If `eval/queries.jsonl`
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isn't populated yet, populate it before changing retrieval — it's
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the most important file in the repo.
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### Standard infrastructure choices
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These are reasoned defaults — only deviate if you have a specific
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need:
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- **Embedding model**: `nomic-embed-text` via Ollama (768-dim,
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free, on-prem)
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- **Reranker**: `jina-reranker-v2-base` GGUF via llama.cpp
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`/v1/rerank` endpoint
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- **Vector store**: Chroma `PersistentClient`
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- **Lexical store**: SQLite FTS5 (stdlib)
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- **Fusion**: Reciprocal Rank Fusion with k=60
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- **Transport**: streamable-HTTP in prod, stdio for local dev
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- **MCP framework**: `mcp.server.mcpserver.MCPServer` (mcp 2.x),
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with `stateless_http=True` passed to `run()`
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- **Container deploy**: Watchtower auto-pull on `:latest`, rollback
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via `:<sha12>` pin
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### Naming the product
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The template uses `PRODUCT_NAME` env var (defaults to `"myproduct"`)
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throughout. Set it on first build. References show up in:
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- `docs_mcp/server.py` — `MCPServer(f"{PRODUCT_NAME}-docs")`
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- Collection name (`<product>_docs`)
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- BM25 db filename
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- Tool names that include the product name (e.g., the `_api_lessons`
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tool — convention is to name it `<product>_api_lessons`)
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Use lowercase, underscores not hyphens, since it ends up in tool
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identifiers that the LLM reads.
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### Image name and package linking are repo-name-derived
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You do NOT need to edit the IMAGE env or the `--package` arg in the
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workflows. Both derive from the repo at runtime via
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`${{ github.repository_owner }}` and
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`${{ github.event.repository.name }}`. So a clone into a repo named
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`my-product-docs` automatically pushes the container as
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`<owner>/my-product-docs:latest` and links the package to its own
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repo. (`github.*` is Gitea Actions' inherited GitHub-Actions
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namespace — the values come from the Gitea server, no github.com
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involvement.)
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The only workflow placeholders you still have to replace per clone
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are the registry endpoints (`REGISTRY_PUSH`, `REGISTRY_PULL`) and
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the Ollama URL, because those depend on the deployment environment,
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not the repo identity.
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## Common commands
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```bash
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# Set up dev environment
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python -m venv venv && source venv/bin/activate
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pip install -r requirements.txt
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# Run the MCP server locally for Claude Desktop dev
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python -m docs_mcp.server --transport stdio
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# Run as HTTP for integration testing
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python -m docs_mcp.server --transport streamable-http --port 8000
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# Rebuild Chroma + BM25 indexes from corpus
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python -m rag.index --rebuild
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# Rebuild only BM25 (fast iteration)
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python -m rag.index --bm25-only
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# Run the eval harness
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python -m eval.run_eval --queries eval/queries.jsonl --output eval/results/baseline.md
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# Generate changelog summary (called by CI, useful locally too)
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python -m scrape.changelog --cached
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python -m scrape.changelog --history-out corpus/.digest/history.jsonl --history-days 120
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```
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## Gotchas (carried forward from the reference build)
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- **`fetch-depth: 0` on `actions/checkout@v4`** in both workflows.
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Default is shallow; history-walking steps (changelog, digest)
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silently produce empty output otherwise. This is the #1 thing
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people miss.
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- **Reranker per-pair token limit**: jina-reranker GGUF rejects the
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ENTIRE batch if any doc exceeds `n_ctx_train=1024`. Truncate docs
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to ~2000 chars before sending to rerank. Full chunk text still
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goes back to the user; truncation is reranking-only.
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- **`stateless_http=True`**: critical for production hosting
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behind Watchtower auto-updates. Without it, every container
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recreate produces a 404 storm from clients with stale session
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IDs. Under mcp 2.x it is a `mcp.run()` kwarg, not a constructor
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arg — along with `host`, `port` and `transport_security`.
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`mcp.settings` no longer exists.
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- **Runner shell is `/bin/sh` (dash)**: no `${VAR::N}` substring
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expansion in workflow scripts. Use `cut`/`awk`/`printf`.
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- **Cloudflare 100 MB body cap**: if pushing through a Cloudflare-
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fronted registry, push via LAN endpoint, pull via public
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hostname. Same registry, different URLs.
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## When the user says...
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| User says | You do |
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|---|---|
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| "Let's start building" / "set up the project" | Read PLAN.md Phase 0; create dirs, requirements.txt, etc. Confirm Python version and existing tooling. |
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| "Build the scraper" / "scrape the docs" | Read PLAN.md Phase 1. Find the upstream portal's underlying API by sniffing; AVOID headless-browser solutions unless the API path is truly closed. |
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| "Get retrieval working" / "make search work" | Read PLAN.md Phase 2-3. Implement chunking, embedder, Chroma indexer, then the three baseline tools. |
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| "Add a reranker" | Read PLAN.md Phase 6. Stand up the llama.cpp sidecar, implement `_rerank()`. Verify with the eval harness. |
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| "Search is missing X queries" | Run the eval harness first to confirm the failure. Then consider: rich chunk-0 rewrites, hybrid retrieval, curated knowledge layer. Don't just tune cosine. |
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| "Let's add hybrid search" | Read PLAN.md Phase 8. Only after you've established the failure mode with eval queries — hybrid is not free. |
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| "Make a tool that submits doc bugs" | Read PLAN.md Phase 12. Find the docs portal's feedback endpoint by sniffing. Build with operator confirmation as a hard requirement in the tool docstring. |
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| "I want a 'what changed' tool" | Read PLAN.md Phase 13. Don't try to do this at runtime — pre-bake the history JSONL at CI time. |
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## Out-of-scope concerns (don't try to solve here)
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- **Reverse proxy / TLS termination** — outside the repo. User
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picks Caddy / Cloudflare Tunnel / nginx / Traefik based on their
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infra.
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- **MetaMCP or other gateway** — outside the repo. Optional, only
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matters when running multiple MCPs.
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- **GPU container orchestration** — outside the repo. Pattern is
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one Ollama container per GPU; the indexer load-balances. Document
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it in deploy/ but don't build it in this template.
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- **Email/blog delivery for weekly_digest** — out of scope per
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PLAN.md ("Out of scope" section). Add a separate script in
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scripts/ if/when the user asks.
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