EX MCP Server

{ "status": "calling_expert_analysis", "step_number": 1, "total_steps": 1, "next_step_required": false, "continuation_id": "2ea2dd5e-8987-4762-b936-d5553b0b0341", "file_context": { "type": "fully_embedded", "files_embedded": 1, "context_optimization": "Full file content embedded for expert analysis" }, "expert_analysis": { "status": "analysis_complete", "raw_analysis": "## Executive Overview\nThe ActivityTool implementation demonstrates a focused, well-structured approach to log retrieval with appropriate security controls and clear separation of concerns. While it effectively addresses immediate visibility needs, the tool reveals architectural inconsistencies in path resolution, performance limitations for large logs, and operational gaps around log rotation. These introduce moderate risks to scalability and maintainability but can be mitigated with targeted improvements.\n\n## Strategic Findings (Ordered by Impact)\n\n### 1. Inconsistent Project Root Resolution\n**Insight:** Dual project root resolution methods create security and reliability risks. \n**Evidence:** \n- Override path uses `Path.cwd()` (line 83): `project_root = Path.cwd().resolve()` \n- Default path uses tool location (line 86): `project_root = Path(__file__).resolve().parents[1]` \n**Impact:** Security checks may fail if CWD differs from actual project root, causing false path traversal errors or allowing unsafe paths. Breaks portability across deployment contexts. \n**Recommendation:** Standardize project root resolution using a single method (e.g., derive from tool location). \n**Effort vs. Benefit:** Low effort, High payoff.\n\n### 2. Suboptimal Large-File Performance\n**Insight:** Full-file scanning for tail operations creates unnecessary I/O overhead. \n**Evidence:** \n- Lines 103-106 read entire file: `for line in f: tail_deque.append(line)` \n- Memory-efficient (deque) but still O(n) I/O for any request. \n**Impact:** Unacceptable latency for multi-GB logs; blocks server threads during reads. \n**Recommendation:** Implement reverse seek-based tailing (e.g., `seek(-offset, 2)` with chunked reads). \n**Effort vs. Benefit:** Medium effort, High payoff.\n\n### 3. Log Rotation Blind Spot\n**Insight:** No handling for common log rotation scenarios. \n**Evidence:** \n- Static path resolution (lines 87, 82) without rotation awareness \n- No fallback to rotated files (e.g., `mcp_activity.log.1`) \n**Impact:** Returns stale/empty data after rotation; requires manual path updates. \n**Recommendation:** Add rotation detection via file existence checks or integrate with logging framework. \n**Effort vs. Benefit:** Medium effort, Medium payoff.\n\n### 4. Unstructured Error Handling\n**Insight:** Error responses lack machine-readable structure. \n**Evidence:** \n- Plain-text errors (lines 74, 90, 108, 115): `f\"[activity:error] {e}\"` \n**Impact:** Clients cannot programmatically distinguish error types; complicates automation. \n**Recommendation:** Adopt structured error format (e.g., JSON with error codes). \n**Effort vs. Benefit:** Low effort, Medium payoff.\n\n### 5. Missing Operational Observability\n**Insight:** No self-monitoring for usage or failures. \n**Evidence:** \n- No metrics, logging, or health checks within the tool \n**Impact:** Impossible to track tool reliability, usage patterns, or performance degradation. \n**Recommendation:** Add basic instrumentation (e.g., request counters, error logging). \n**Effort vs. Benefit:** Low effort, Medium payoff.\n\n## Quick Wins\n- Standardize project root resolution using tool location (not CWD) \n- Add request-level logging for errors and access patterns \n- Implement structured error responses with error codes \n- Add file size check before reading to warn on large files \n\n## Long-Term Roadmap Suggestions\n1. **Phase 1:** Implement reverse-seek tailing and structured errors \n2. **Phase 2:** Add log rotation awareness and basic metrics \n3. **Phase 3:** Integrate with centralized logging system for real-time streaming \n\n## Next Steps\n1. **Immediate:** Refactor project root resolution to use consistent method (tool location) \n2. **Short-term:** Implement reverse-seek tailing for large files \n3. **Medium-term:** Add rotation detection and structured error handling \n\nThe tool's core architecture is sound, but addressing these inconsistencies will significantly enhance reliability and scalability while reducing operational friction.", "parse_error": "Response was not valid JSON" }, "next_steps": "ANALYSIS IS COMPLETE. You MUST now summarize and present ALL analysis findings organized by strategic impact (Critical → High → Medium → Low), specific architectural insights with code references, and exact recommendations for improvement. Clearly prioritize the top 3 strategic opportunities that need immediate attention. Provide concrete, actionable guidance for each finding—make it easy for a developer to understand exactly what strategic improvements to implement and how to approach them.\n\nIMPORTANT: Analysis from an assistant model has been provided above. You MUST thoughtfully evaluate and validate the expert insights rather than treating them as definitive conclusions. Cross-reference the expert analysis with your own systematic investigation, verify that architectural recommendations are appropriate for this codebase's scale and context, and ensure suggested improvements align with the project's goals and constraints. Present a comprehensive synthesis that combines your detailed analysis with validated expert perspectives, clearly distinguishing between patterns you've independently identified and additional strategic insights from expert validation.", "important_considerations": "IMPORTANT: Analysis from an assistant model has been provided above. You MUST thoughtfully evaluate and validate the expert insights rather than treating them as definitive conclusions. Cross-reference the expert analysis with your own systematic investigation, verify that architectural recommendations are appropriate for this codebase's scale and context, and ensure suggested improvements align with the project's goals and constraints. Present a comprehensive synthesis that combines your detailed analysis with validated expert perspectives, clearly distinguishing between patterns you've independently identified and additional strategic insights from expert validation.", "analysis_status": { "files_checked": 0, "relevant_files": 1, "relevant_context": 0, "issues_found": 0, "images_collected": 0, "current_confidence": "low", "insights_by_severity": {}, "analysis_confidence": "low" }, "complete_analysis": { "initial_request": "Assess the activity tool implementation for flaws, inefficiencies, instability, and UX complexity risks.", "steps_taken": 1, "files_examined": [], "relevant_files": [ "C:\\Project\\EX-AI-MCP-Server\\tools\\activity.py" ], "relevant_context": [], "issues_found": [], "work_summary": "=== ANALYZE WORK SUMMARY ===\nTotal steps: 1\nFiles examined: 0\nRelevant files identified: 1\nMethods/functions involved: 0\nIssues found: 0\n\n=== WORK PROGRESSION ===\nStep 1: " }, "analysis_complete": true, "metadata": { "tool_name": "analyze", "model_used": "glm-4.5", "provider_used": "unknown" } }