Provides practical code examples and guides for leveraging the Claude API to build and enhance AI applications.
Streamline AI-driven development workflows by automating task management with Claude.
Provides code examples and guides for building applications with Claude, Anthropic's AI assistant.
Facilitates rapid development of deployable applications using the Anthropic API.
Provides convenient synchronous and asynchronous access to the Anthropic REST API for Python 3.9+ applications.
Automates complex engineering tasks by integrating with developer tools and leveraging AI for planning, execution, and iteration.
Connects Claude Desktop to read and search your Obsidian vault's Markdown notes.
Secures AI agents by providing an egress proxy with DLP scanning, SSRF protection, MCP response scanning, and workspace integrity monitoring.
Enables Claude Desktop to interact directly with Figma, allowing for AI-assisted design workflows.
Provides visual context to agentic coding tools by allowing users to select browser DOM elements and feeding their data to AI.
Enables tool use and function calling with Anthropic models, facilitating interaction with external resources.
Provides an MCP server to load and expose Anthropic-style skills for non-Claude clients.
Provides a local, open-source coding assistant experience similar to Claude Code, leveraging the Vercel AI SDK.
Implements Claude Code-like functionality using the Model Context Protocol, enabling code understanding, modification, and execution.
Provides a long-term memory layer for AI agents, automatically learning and recalling project context across sessions.
Implements Claude Code's software engineering capabilities as a Model Context Protocol (MCP) server.
Integrates with the Postman API to enable comprehensive management of Postman collections, environments, and APIs.
Decompose complex software projects into parallel executable tasks using an AI-powered cascading development framework.
Orchestrates AI coding agents like Claude Code CLI and Gemini CLI to automate and manage complex coding tasks.
Provides example implementations of Model Context Protocol (MCP) Streamable HTTP client and server in Python and TypeScript.
Scroll for more results...