feat: implement MCP sampling for semantic search RAG (ADR-008)

Add nc_notes_semantic_search_answer tool that combines semantic search
with MCP sampling to generate natural language answers from retrieved
Nextcloud Notes. This enables Retrieval-Augmented Generation (RAG)
patterns without requiring a server-side LLM.

Key features:
- Client-side LLM generation via ctx.session.create_message()
- Graceful fallback when sampling unavailable
- Proper source citations in generated answers
- No results optimization (skips sampling when no docs found)
- Comprehensive unit and integration tests

Implementation details:
- SamplingSearchResponse model with generated_answer and sources
- Fixed prompt template with document context and citation instructions
- Model preferences hint Claude Sonnet for balanced performance
- Falls back to returning documents without answer on sampling failure

Updates:
- Add ADR-008 documenting sampling architecture decision
- Add MCP sampling pattern guidance to CLAUDE.md
- Update README.md and docs/notes.md (7 → 9 tools)
- Add 4 unit tests and 6 integration tests

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

docs/notes.md

@@ -8,7 +8,9 @@
 | `nc_notes_update_note` | Update an existing note by ID |
 | `nc_notes_append_content` | Append content to an existing note with a clear separator |
 | `nc_notes_delete_note` | Delete a note by ID |
-| `nc_notes_search_notes` | Search notes by title or content |
+| `nc_notes_search_notes` | Search notes by title or content (keyword search) |
+| `nc_notes_semantic_search` | Search notes by meaning using vector embeddings (requires vector sync) |
+| `nc_notes_semantic_search_answer` | Search notes semantically and generate a natural language answer via MCP sampling (requires vector sync and sampling-capable MCP client) |
 
 ### Note Attachments