Provides structured guidance for fixing issues during the ITERATE phase of development workflows, helping enforce disciplined programming practices through verified outputs.
Analyze and resolve issues by generating tailored prompts for root cause analysis and fixes, supporting optional instructions and version-specific templates.
Analyze code for quality and issues by specifying the programming language and analysis type. Improve code structure and identify potential problems with this AI-driven tool.
CodeGuard MCP is a real-time AI code security scanning tool used to detect vulnerabilities, keys, and compliance issues in AI-generated code, and is suitable for code security reviews in development environments
A lightweight Model Context Protocol (MCP) orchestrator designed for efficiency at scale. It features TOON compression (reducing token usage by 30-90%) and Lazy Loading, making it the ideal solution for complex, multi-tool agentic workflows.
Enables AI-driven job application automation for LinkedIn and SEEK platforms with intelligent cover letter generation, automated application submission, and application tracking management. Supports anti-detection measures and complies with platform usage policies for safe job hunting automation.