Overhaul docs retrieval and web search quality

Replace the abandoned llms-txt-mcp/Chroma docs backend with an in-repo
MCP service: SQLite WAL + FTS5 + sentence-transformer embeddings,
transactional source replacement, persisted state across restarts,
singleflight refresh with conditional requests, hybrid lexical/semantic
ranking with exact-duplicate collapse, source/host filters, and
explicit-by-default content retrieval. Add docs_rebuild and a
docs-rebuild CLI command.

Add deterministic llms-full.txt snapshot generation for machine-local
menus with hash-validated provenance manifests; lifecycle commands
promote a local menu to its snapshot only when the manifest validates.
Switch public source profiles to content-bearing llms-full.txt feeds.

Improve web search: bounded provider fallback with per-attempt
diagnostics and cancellation, an optional Brave Search API provider,
strict SearXNG engine selection, capped link/media extraction, and a
real engine=browser renderer that routes every request through the
existing SSRF vetting while blocking WebSockets, non-GET traffic, and
private destinations.

Extend release checks with offline unit suites and isolated candidate
container tests for both images.

docker/docs/context_docs/models.py

@@ -0,0 +1,122 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+
+import numpy as np
+
+
+@dataclass(frozen=True)
+class ParsedDocument:
+    title: str
+    description: str
+    content: str
+    canonical_url: str
+    heading_path: str
+    chunk_index: int = 0
+
+
+@dataclass(frozen=True)
+class ParsedSource:
+    format: str
+    documents: list[ParsedDocument]
+
+
+@dataclass(frozen=True)
+class FetchResponse:
+    status: int
+    requested_url: str
+    resolved_url: str
+    body: str = ""
+    etag: str | None = None
+    last_modified: str | None = None
+
+
+@dataclass(frozen=True)
+class PreparedDocument:
+    id: str
+    configured_source: str
+    resolved_source: str
+    source_host: str
+    canonical_url: str
+    canonical_host: str
+    title: str
+    description: str
+    heading_path: str
+    content: str
+    content_hash: str
+    embedding: np.ndarray
+
+
+@dataclass(frozen=True)
+class SourceUpdate:
+    configured_source: str
+    resolved_source: str
+    etag: str | None
+    last_modified: str | None
+    body_hash: str
+    raw_body: str
+    parser_fingerprint: str
+    embedding_fingerprint: str
+    checked_at: float
+    indexed_at: float
+    stale_at: float
+    documents: list[PreparedDocument]
+
+
+@dataclass(frozen=True)
+class SourceState:
+    configured_source: str
+    resolved_source: str | None
+    active: bool
+    etag: str | None
+    last_modified: str | None
+    body_hash: str | None
+    raw_body: str | None
+    parser_fingerprint: str | None
+    embedding_fingerprint: str | None
+    checked_at: float | None
+    indexed_at: float | None
+    stale_at: float | None
+    last_error: str | None
+    doc_count: int
+
+
+@dataclass(frozen=True)
+class StoredDocument:
+    id: str
+    configured_source: str
+    resolved_source: str
+    source_host: str
+    canonical_url: str
+    canonical_host: str
+    title: str
+    description: str
+    heading_path: str
+    content: str
+    content_hash: str
+    embedding: np.ndarray
+
+
+@dataclass(frozen=True)
+class SearchResult:
+    id: str
+    configured_source: str
+    canonical_url: str
+    title: str
+    description: str
+    heading_path: str
+    content: str
+    content_hash: str
+    score: float
+    lexical_rank: int | None
+    semantic_rank: int | None
+    duplicate_count: int = 1
+    alternate_sources: list[dict[str, str]] = field(default_factory=list)
+
+
+@dataclass(frozen=True)
+class RefreshOutcome:
+    source: str
+    status: str
+    document_count: int
+    detail: str | None = None