Local-only MCP server exposing fast code navigation, reading, and editing tools over STDIO.
Command-Line Interface for Firebase
Model Context Protocol implementation for TypeScript
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The **Model Context Protocol (MCP) client** for the [AI SDK](https://ai-sdk.dev/docs) lets you connect to MCP servers and use their tools with AI SDK functions like `generateText` and `streamText`.
Official MCP server for Notion API
NestJS module for creating Model Context Protocol (MCP) servers
A utility MCP server providing JSON formatting, Base64/URL encoding, hashing, JWT decoding, regex testing, timestamp conversion, text transforms, color conversion, diff generation, and random generation — all accessible to AI agents via MCP.
Playwright Tools for MCP
MCP server for Chrome DevTools
Azure MCP Server - Model Context Protocol implementation for Azure, for win32 on x64
MCP server for Agentation - visual feedback for AI coding agents
MCP server that exercises all the features of the MCP protocol
Tools for building MCP Bundles
Azure MCP Server - Model Context Protocol implementation for Azure, for linux on x64
LangChain.js adapters for Model Context Protocol (MCP)
Framework for building Model Context Protocol (MCP) servers in Typescript
MCP server for SAPUI5/OpenUI5 development
MCP server for interacting with Azure DevOps
Tools for writing MCP clients and servers without pain
(For Interal Use Only) Provided MCP Tools for code analysis and improvement of LWC components
MCP server for interacting with Datadog API
Stitch MCP CLI helper. Automates Google Cloud authentication. Generates MCP config for your client. Sets up a proxy server.
rails-ai-context turns your running Rails app into the source of truth for AI coding assistants. Instead of guessing from training data or stale file reads, agents query 38 live tools (via MCP server or CLI) to get your actual schema, associations, routes, inherited filters, conventions, and test patterns. Semantic validation catches cross-file errors (wrong columns, missing partials, broken routes) before code runs — so AI writes correct code on the first try. Auto-generates context files for Claude Code, Cursor, GitHub Copilot, OpenCode, and Codex CLI. Works standalone or in-Gemfile.
Gives an easy way to expose your Foobara commands to tools like Claude Code via the Model Context Protocol (MCP)
A RubyLLM provider that implements OpenAI's Responses API, providing access to built-in tools (web search, code interpreter, file search, shell, apply patch), stateful conversations, server-side compaction, containers API, background mode, and MCP support.
ClaudeAgent is a Ruby SDK for building autonomous AI agents that interact with Claude Code CLI. It provides both simple one-shot queries and interactive bidirectional sessions with support for tool use, hooks, permissions, and in-process MCP servers.
Rails Active MCP enables secure Rails console access through Model Context Protocol (MCP) for AI agents and development tools like Claude Desktop. Provides safe database querying, model introspection, and code execution with comprehensive safety checks and audit logging. Features include: • Safe Ruby code execution with configurable safety checks • Read-only database query tools with result limiting • Rails model introspection (schema, associations, validations) • Dry-run code analysis for safety validation • Environment-specific configuration presets • Comprehensive audit logging and monitoring • Claude Desktop integration out of the box
An MCP (Model Context Protocol) server that provides LLM agents with access to runtime context of executing Ruby processes. Connect to debug sessions, evaluate code, inspect objects, and control execution flow via MCP tools.
Claude Swarm enables you to run multiple Claude Code instances that communicate with each other via MCP (Model Context Protocol). Create AI development teams where each instance has specialized roles, tools, and directory contexts. Define your swarm topology in simple YAML and let Claude instances collaborate across codebases. Perfect for complex projects requiring specialized AI agents for frontend, backend, testing, DevOps, or research tasks.
pikuri-core is the lean, audit-friendly foundation of the pikuri family: Pikuri::Agent (a thin wrapper around ruby_llm's chat loop) with its Configurator + Extension protocol, the strict Pikuri::Tool framework, a listener surface for rendering / budgets / sub-agents, and four bundled stateless tools (calculator, web search, web scrape, fetch). Extensions (skills, MCP, workspace, coding stack, named-agent personas) live in sibling gems so a privacy-conscious user can install just this core and audit a minimal dependency tree. For the convenience bundle that pulls in everything, see the +pikuri+ metagem.
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