Graph memory for AI agents — context engine for OpenClaw + MCP server for Claude Code/Claude.ai
The tRPC server library
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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`.
AI SDK by Vercel - build apps like ChatGPT, Claude, Gemini, and more with a single interface for any model using the Vercel AI Gateway or go direct to OpenAI, Anthropic, Google, or any other model provider.
Detect if code is running in an AI agent or automated development environment
The Gateway provider for the [AI SDK](https://ai-sdk.dev/docs) allows the use of a wide variety of AI models and providers.
The **[Anthropic provider](https://ai-sdk.dev/providers/ai-sdk-providers/anthropic)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Anthropic Messages API](https://docs.anthropic.com/claude/reference/messages_post).
Deep Agents - a library for building controllable AI agents with LangGraph
A collection of essential TypeScript types
The **[Google Generative AI provider](https://ai-sdk.dev/providers/ai-sdk-providers/google-generative-ai)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Google Generative AI](https://ai.google/discover/generativeai/)
The **[OpenAI provider](https://ai-sdk.dev/providers/ai-sdk-providers/openai)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the OpenAI chat and completion APIs and embedding model support for the OpenAI embeddings API.
This package provides a foundation for implementing providers that expose an OpenAI-compatible API.
Promptbook: Create persistent AI agents that turn your company's scattered knowledge into action
A agent component for Convex.
Structured diagnostic code library
LangGraph
The AssemblyAI JavaScript SDK provides an easy-to-use interface for interacting with the AssemblyAI API, which supports async and real-time transcription, as well as the latest LeMUR models.
Azure AI Projects client library.
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The **[Google Vertex provider](https://ai-sdk.dev/providers/ai-sdk-providers/google-vertex)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the [Google Vertex AI](https://cloud.google.com/vertex-ai) APIs.
Azure AI Agents client library.
The **[Mistral provider](https://ai-sdk.dev/providers/ai-sdk-providers/mistral)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the Mistral chat API.
Claude Code governance framework that applies guardrails, guidance, and automated enforcement to projects
ace-git gives developers and coding agents focused git context commands and guided workflows for rebases, pull requests, and commit reorganization, with smart diff output and Git 2.23+ guardrails.
Superkick wraps AI coding CLIs in a PTY proxy and injects CI results, PR reviews, and other external context — right when the agent is ready to hear it.
Build AI agents with declarative DSL and Model Context Protocol support
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.
A Model Context Protocol (MCP) server that enables AI agents to query information about gems in a Ruby project's Gemfile, including source code and metadata.
A terminal interface to interactively search, select, and bundle markdown notes for AI agent context.
RubyPi is a minimal, composable AI agent harness for Ruby. Build production-ready LLM agents and AI agents with a unified provider interface across OpenAI, Anthropic Claude, and Google Gemini, plus first-class support for tool calling (function calling), streaming responses, automatic retries, provider fallback, context compaction, and a think-act-observe agent loop. Anti-framework design — small, idiomatic, and explicit. Ideal for building autonomous AI agents, ReAct agents, tool-using LLM agents, and chatbots in Ruby.
KairosChain is a Model Context Protocol (MCP) server for self-managed, evolvable AI skill definitions. It combines Pure Skills design (Ruby DSL/AST) with a private blockchain, enabling AI agents to define, evolve, and audit their own capabilities through self-referential skill management. Supports stdio and Streamable HTTP transport.
Plugin engine providing OpenAI-compatible /v1/chat/completions and /v1/models endpoints using Collavre AI agents with context injection.
Rails Engine that captures exceptions, stores them in your database with rich context, and exposes error data via a bundled MCP server so AI agents can triage, resolve, and fix errors autonomously.
A Model Context Protocol (MCP) server that allows AI agents to start, stop, and monitor Rails development servers
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.
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