Adds human-readable `title` and categorization `tags` to all ~24 @mcp.tool
decorators across the MCP tools package. FastMCP 3.3.1 (pinned in pyproject.toml)
supports both fields natively. Tags used: notes, search, projects, cloud, schema,
navigation, canvas, ui.
Extends test_tool_contracts.py with an async test that asserts every registered
tool has a non-empty title and at least one tag to prevent future regressions.
output_schema is explicitly deferred as a follow-up (phase 2): it requires
per-tool design decisions about which tools reliably return structured JSON and
how to handle tools that return str|dict depending on output_format.
Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: Drew Cain <groksrc@gmail.com>
feat: Add multiple projects support
feat: enhanced read_note for when initial result is not found
fix: merge frontmatter when updating note
fix: handle directory removed on sync watch
## Summary
- Add comprehensive documentation to all MCP prompt modules
- Enhance search prompt with detailed contextual output formatting
- Implement consistent logging and docstring patterns across prompt
utilities
- Fix type checking in prompt modules
## Prompts Added/Enhanced
- `search.py`: New formatted output with relevance scores, excerpts, and
next steps
- `recent_activity.py`: Enhanced with better metadata handling and
documentation
- `continue_conversation.py`: Improved context management
## Resources Added/Enhanced
- `ai_assistant_guide`: Resource with description to give to LLM to
understand how to use the tools
## Technical improvements
- Added detailed docstrings to all prompt modules explaining their
purpose and usage
- Enhanced the search prompt with rich contextual output that helps LLMs
understand results
- Created a consistent pattern for formatting output across prompts
- Improved error handling in metadata extraction
- Standardized import organization and naming conventions
- Fixed various type checking issues across the codebase
This PR is part of our ongoing effort to improve the MCP's interaction
quality with LLMs, making the system more helpful and intuitive for AI
assistants to navigate knowledge bases.
🤖 Generated with [Claude Code](https://claude.ai/code)
---------
Co-authored-by: phernandez <phernandez@basicmachines.co>
Drew Cain