The MCP Probe Kit is a powerful Model Context Protocol server offering 40 practical tools that enhance code quality, development efficiency, and project management while streamlining the skills documentation process.
claude install mybolide/mcp-probe-kitThe MCP Probe Kit is a powerful Model Context Protocol server offering 40 practical tools that enhance code quality, development efficiency, and project management while streamlining the skills documentation process.
[{"step":"Install and configure the MCP Probe Kit server in your development environment. Ensure it has access to your project's root directory and all necessary dependencies (e.g., linters, security scanners).","action":"Run `pip install mcp-probe-kit` and initialize with `mcp-probe-kit --init --project-path /path/to/your/project`","tip":"For Dockerized projects, mount your project directory as a volume and run the probe kit container with the same user permissions as your development environment."},{"step":"Define the scope of analysis by specifying the programming language, critical file paths, or modules you want to focus on. Use the prompt template to customize the output format and priorities.","action":"Replace [PROJECT_NAME], [LANGUAGE], and other placeholders in the prompt template with your specific requirements.","tip":"For large projects, break the analysis into smaller chunks (e.g., by microservice or module) to avoid timeouts and improve focus."},{"step":"Execute the analysis using the configured prompt. Review the generated report for critical issues first, then address lower-priority findings.","action":"Paste the customized prompt into your AI assistant (e.g., Claude Code) and run it. Save the output to a file for later reference.","tip":"Use the `--output-format json` flag if you plan to integrate the results with other tools like Mode for visualization."},{"step":"Integrate the probe kit into your CI/CD pipeline to run automated checks on every pull request. Configure thresholds for blocking builds based on critical findings.","action":"Add a step in your GitHub Actions or GitLab CI workflow to run `mcp-probe-kit --ci-mode --fail-on=critical` before merging.","tip":"Set up a dashboard in Mode to track trends in code quality metrics over time, correlating them with deployment frequency and bug reports."},{"step":"Schedule regular deep-dive sessions (e.g., monthly) to review the full report and plan refactoring efforts. Use the probe kit's findings to prioritize technical debt reduction.","action":"Create a recurring task in your project management tool (e.g., Jira) to review the probe kit report and assign refactoring tickets based on the priority action plan.","tip":"Combine the probe kit's output with Mode to create visualizations showing the impact of refactoring efforts on performance and maintainability."}]
Improving code quality through automated checks
Enhancing development efficiency with integrated tools
Streamlining project management workflows
Generating comprehensive skills documentation
claude install mybolide/mcp-probe-kitgit clone https://github.com/mybolide/mcp-probe-kitCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use the MCP Probe Kit to analyze the [PROJECT_NAME] codebase and generate a detailed report covering: 1) Code quality metrics (cyclomatic complexity, duplication, maintainability index) for [LANGUAGE], 2) Security vulnerabilities in [FILE_PATHS_OR_MODULES], 3) Performance bottlenecks in [SPECIFIC_FUNCTIONS_OR_ENDPOINTS], and 4) Documentation gaps for [PUBLIC_APIS_OR_MODULES]. Prioritize findings by impact and suggest remediation steps with code examples where applicable.
### MCP Probe Kit Analysis Report: Acme Corp E-Commerce Platform
**Project Overview:** Analyzed 47,218 lines of Python/Django code across 1,242 files (85% test coverage). Primary focus on `/src/api/` (REST endpoints) and `/src/utils/` (shared libraries).
#### 1. Code Quality Metrics
- **Cyclomatic Complexity:** 1,842 total (target: < 10 per function). Critical offenders:
- `src/api/views/order_processing.py::process_payment()` (complexity: 47) - Refactor into 4 smaller functions
- `src/utils/email_templates.py::generate_receipt()` (complexity: 32) - Replace nested conditionals with strategy pattern
- **Duplication:** 12.4% (target: < 5%). Highest in `/src/api/serializers/` (38% duplication in User-related serializers)
- **Maintainability Index:** 68.2/100 (borderline). 214 files scored < 50 (critical threshold)
#### 2. Security Vulnerabilities (CVSS Score ≥ 6.0)
- **SQL Injection:** Detected in `src/api/views/product_search.py` (line 89) - Uses raw SQL with user input. **Fix:** Migrate to Django ORM
- **Hardcoded Secrets:** 3 instances of API keys in `/src/config/prod.py` (exposed in Git history)
- **CSRF Protection Missing:** 17 endpoints lack `@csrf_exempt` or proper token validation
- **Recommendation:** Implement Django's `django-csp` and rotate all exposed credentials via AWS Secrets Manager
#### 3. Performance Bottlenecks
- **Database Queries:** `/api/v2/orders/` averages 2.4s response time due to N+1 queries in `OrderSerializer`
- **Fix:** Implement `prefetch_related('order_items__product')`
- **Memory Leaks:** `src/workers/export_service.py` consumes 2.1GB RAM during large CSV exports
- **Fix:** Use `pandas.read_csv(chunksize=10000)` instead of loading entire file
- **API Rate Limiting:** `/api/v1/search/` hit 95% of 100 requests/minute quota during peak traffic
#### 4. Documentation Gaps
- **Missing:** Swagger/OpenAPI specs for 42 endpoints (68% coverage target)
- **Outdated:** `/docs/api/authentication.md` references deprecated OAuth2 flow
- **Recommendation:** Generate specs automatically using `drf-yasg` and add versioning to docs
#### Priority Action Plan
1. **Week 1:** Address SQL injection and hardcoded secrets (P0)
2. **Week 2:** Refactor high-complexity functions (P1)
3. **Week 3:** Implement query optimization and rate limiting (P2)
4. **Ongoing:** Add automated security scanning to CI/CD pipeline
**Tools Used:** MCP Probe Kit v2.1.3, Bandit (security), Django Debug Toolbar (performance)
**Next Steps:** Review with team leads by EOD Friday. Full report available at `/reports/mcp-probe-2024-05-15.html`Unlock data insights with interactive dashboards and collaborative analytics capabilities.
Orchestrate workloads with multi-cloud support, job scheduling, and integrated service discovery features.
Serverless MySQL database platform
Design, document, and generate code for APIs with interactive tools for developers.
CI/CD automation with build configuration as code
Enhance performance monitoring and root cause analysis with real-time distributed tracing.
Take a free 3-minute scan and get personalized AI skill recommendations.
Take free scan