Provides tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.
Enables automation of workflows across GitHub, Notion, and Google Calendar with AI-powered task execution, personalized agent memory, and Slack integration for seamless team coordination and project management.
Enables LLMs to retrieve, analyze, and programmatically implement CodeRabbit AI code review suggestions on GitHub pull requests, with automated workflows for processing and resolving review comments.
Code Reviewer AI - MCP server providing AI-powered tools and automation by MEOK AI Labs
Enables comprehensive GitHub PR reviews through Cursor's AI by fetching PR diffs, running static analysis tools (ESLint, Prettier, TypeScript, Semgrep), executing tests, and generating detailed code review reports with inline comments.
Enables AI agents to autonomously create and manage topic-specific vector knowledge bases with end-to-end functionality including project creation, content ingestion from URLs, semantic search, and progress tracking. Provides a complete research workflow without exposing low-level APIs.
An MCP server to create secure code sandbox environment for executing code within Docker containers. This MCP server provides AI applications with a safe and isolated environment for running code while maintaining security through containerization.
A secure Model Context Protocol server that allows AI assistants and LLM applications to safely execute Python and JavaScript code snippets in containerized environments.
Enables LLMs to perform high-performance code search and analysis across multiple languages using symbol indexing, regex text search, and structural AST pattern matching. It also provides tools for technology stack detection and dependency analysis with persistent caching for optimized performance.
High-performance code understanding toolkit that enables batch reading of multiple files with dependency context, structural outline extraction with Java annotation awareness, and precise location of classes/methods across large codebases.
Provides semantic code intelligence to help users search, navigate, and analyze entire codebases using plain English. It enables Claude to perform architectural overviews, bug detection, and refactor suggestions through local semantic search and keyword indexing.
Enables AI agents to efficiently read Python code by first providing file skeletons then fetching only needed implementations, reducing noise and cost.
A MCP server for managing and storing code snippets in various programming languages, allowing users to create, list, and delete snippets via a standardized interface.
Enables CODESYS development assistance via MCP, including curated guidance, Structured Text writing help, local PDF search, and live official documentation lookup.
Exposes the codetoprompt library to LLM agents for generating comprehensive prompts from directories and retrieving specific file contents. It enables codebase analysis through detailed statistics like token counts and file type breakdowns.
A stateful, AST-aware MCP server for structured code review workflows. It enables iterative review sessions with AST-based context localization and provides structured feedback with verdicts and patch suggestions for JavaScript/TypeScript code.
AI-powered code-review toolkit: MCP server + CLI to analyze GitHub PRs with local LLM smells, cloud LLM summaries, inline comments, risk gating, and test stub generation.
Codevira MCP provides persistent memory and project context for AI coding agents by maintaining a shared knowledge base of decisions, roadmaps, and code relationships across sessions. It enables semantic code search and automated context tracking to ensure consistency and reduce token overhead during complex development tasks.
An MCP server that indexes Python codebase structures to help AI assistants discover and reuse existing functions instead of duplicating code. It enables real-time searching of function metadata, duplicate detection, and structural analysis across multiple projects.
Generates narrated video walkthroughs of git commits, staged/unstaged changes, or entire codebases with AI-powered analysis, syntax-highlighted code visualization, and text-to-speech narration.
