❓ Did you really test this MCP server? A Fair Critique #10
Description
Real Talk: Critical Evaluation of Context Processor
SUPERVISION MODEL: This issue is an Epic. Use @claude in comments to delegate tasks.
Progress: 1 of 10 tasks completed (✅ #14)
✅ What Works Well
- Tests exist - 81 unit tests covering core functionality (now 101 with integration tests)
- Type safety - Full TypeScript with proper typing
- MCP integration - Correctly implements Model Context Protocol
- Simple storage - File-based JSON works for small use cases
- Basic operations - Save/load/delete work as expected
- Integration tests - 20 new MCP protocol compliance tests ✅
🟡 Serious Concerns & Linked Tasks
1. No Real Integration Testing → Task #14
✅ COMPLETED (PR #26) - 20 automated integration tests + manual IDE testing guide
Only unit tests, no tests against actual MCP clients (Claude, Cursor, etc.)
2. Pre-Processing is Superficial
- Clarify strategy: Just regex-based vague word detection
- Analyze strategy: Simple word counts and complexity heuristics
- Search strategy: Keyword extraction via frequency, not semantic
- Fetch strategy: Naive URL regex matching
3. Scaling Will Fail → Task #15
File-based storage with 81+ tests might have race conditions. Testing 100K files needed.
4. Search is Broken for Real Use → Task #16
Tag search is exact match. No full-text search or semantic similarity.
5. Storage Architecture is Questionable → Task #20
10K contexts = 10K files. No compression, encryption, or optimization.
6. Error Handling is Minimal → Task #17
What happens if disk is full? JSON corrupted? Permissions change?
7. Documentation is AI-Generated → Task #23
Wiki pages are comprehensive but untested. Examples aren't run in CI.
8. Performance is Unproven → Task #22
No benchmarks. "Typical 50ms save time" is not verified. Unknown behavior at scale.
9. No Production Features → Task #18
No logging, metrics, monitoring hooks, graceful shutdown, or health checks.
10. Models Are Hardcoded
Can't add custom models at runtime. Must edit context-models.json.
📋 Task Breakdown (Use @claude to delegate)
| # | Task | Issue | Status |
|---|---|---|---|
| 1 | Integration Testing | #14 | ✅ Complete |
| 2 | Scaling & Load Testing | #15 | ⏳ Pending |
| 3 | Search Improvement | #16 | ⏳ Pending |
| 4 | Error Handling | #17 | ⏳ Pending |
| 5 | Logging & Monitoring | #18 | ⏳ Pending |
| 6 | Concurrency Control | #19 | ⏳ Pending |
| 7 | Database Alternative | #20 | ⏳ Pending |
| 8 | Security Review | #21 | ⏳ Pending |
| 9 | Performance Profiling | #22 | ⏳ Pending |
| 10 | Documentation Testing | #23 | ⏳ Pending |
🎯 How to Use This Epic
For the Supervisor (You):
- Review a task by opening its issue (e.g., Task #2: Scaling & Load Testing - 10K+ Contexts #15)
- Comment:
@claude implement this task - GitHub Actions will detect it and create a task branch
- Review the PR when ready
- Merge when satisfied
For Claude (Implementation):
- Watch for @claude mentions
- Create comprehensive solutions
- Follow existing code patterns
- Write tests
- Update documentation
Bottom Line
This is a good learning project but not production-ready. This epic tracks the path to production readiness.
Progress: 1/10 tasks complete (10%)
Last Updated: 2025-11-26
Epic Status: In Progress (1 of 10 completed)