Browse 27 tools for your AI coding workflow.
Query anything (GitHub, Notion, Google Sheets, +40 services) with SQL and connect LLMs via MCP.
Open-source LLM app development platform. Build AI workflows, RAG pipelines, and agents with a visual interface.
AI-powered multi-agent system that automatically analyzes codebases and generates comprehensive documentation. Features GitLab integration, concurrent processing, and multiple LLM support for better code understanding and developer onboarding.
Optimize markdown documentation for LLMs and RAG systems, reducing token consumption by 67-95%.
A fast Rust CLI for codebase metrics, AST-compressed LLM context bundles, and a built-in MCP server.
An LLM-powered framework for automated repository-level code documentation generation.
AI-first security scanner with 9,600+ detection rules for AI/ML, LLM agents, and MCP servers.
A frontend UI solution for the AI era, including UI protocols, rendering SDKs, and component libraries for Generative UI, AI Agents, and LLM applications.
MCP server for browser automation using Playwright, enabling LLMs to interact with web pages.
An open-source, extensible AI agent that goes beyond code suggestions to install, execute, edit, and test with any LLM.
Up-to-date code documentation for LLMs and AI code editors, eliminating outdated or hallucinated API references.
Build stateful, multi-actor AI agents with graph-based workflows. From LangChain, the most popular LLM framework.
MCP server for semantic code research and context generation using LLM patterns across public and private repos.
An MCP server that enables LLMs to index, search, and analyze code repositories with minimal setup.
A fast Rust tool to serialize text files in a repo for LLM consumption.
An MCP server that exposes llms.txt files to IDEs for context-aware development.
A JADX plugin and MCP server for analyzing Android APKs with LLMs like Claude.
Drag-and-drop UI for building LLM flows and AI agents. Visual LangChain builder with no-code interface.
A unified LLM-agent skill for code review covering security (CWE) and privacy (GDPR) via a detector-validator methodology.
A tool that solves the context management gap for LLMs by organizing codebase information into structured documents.
