Metal MCP Server
by aldrin-labs
# MCP-WebResearch Improvements Plan
## Phase 1: High Priority Improvements
### 1. Intelligent Search Queue System [IN PROGRESS]
Implementation Steps:
1. Create SearchQueue class to manage search operations
- Add queue data structure for pending searches
- Implement rate limiting with exponential backoff
- Add progress tracking and status reporting
- Handle error recovery and retries
2. Add new tool endpoints:
- batch_search: Queue multiple searches
- get_queue_status: Check search queue progress
- cancel_search: Cancel pending searches
3. Enhance search results aggregation:
- Implement result deduplication
- Add result sorting options
- Improve error handling and recovery
4. Add queue persistence:
- Save queue state between sessions
- Handle interrupted searches
- Implement queue recovery
Testing Criteria:
- Queue should handle at least 50 searches without triggering anti-bot measures
- Rate limiting should adapt to Google's response patterns
- Progress updates should be accurate and timely
- Results should be properly aggregated and deduplicated
### 2. Enhanced Content Extraction & Relevance Scoring [IN PROGRESS]
Implementation Steps:
1. Improve content relevance scoring:
- Implement TF-IDF scoring
- Add keyword proximity analysis
- Add content section weighting
- Implement readability scoring
2. Enhance content extraction:
- Improve HTML structure parsing
- Add support for common content patterns
- Implement better content cleaning
- Add structured data extraction
3. Add content summarization:
- Implement extractive summarization
- Add key points extraction
- Generate section summaries
- Preserve important metadata
4. Improve markdown conversion:
- Enhance formatting preservation
- Better handle tables and lists
- Improve code block handling
- Better preserve document structure
Testing Criteria:
- Content relevance scores should align with human judgment
- Extracted content should be clean and well-formatted
- Structured data should be accurately identified
- Summaries should capture key information
- Markdown output should be consistently formatted
## Implementation Notes:
- Each feature will be implemented incrementally
- Testing will be done after each major component
- Code reviews required before merging
- Performance benchmarks will be maintained
## Status Tracking:
[ ] Feature 1 Started
[ ] Feature 1 Tested
[ ] Feature 1 Complete
[ ] Feature 2 Started
[ ] Feature 2 Tested
[ ] Feature 2 Complete
## Dependencies to Add:
- tf-idf-search (for relevance scoring)
- readability (for content analysis)
- html-to-md (for improved markdown conversion)
- rate-limiter-flexible (for queue management)