294 boosters for "agents" — AI-graded, open source, ready to install
Forage is a self-improving tool discovery system that enables AI agents to automatically find, install, and learn to use new tools without manual configuration. It benefits developers building extensible AI applications and agents that need dynamic capability expansion.
TakoData Tako MCP enables AI agents to query and visualize real-time data by integrating Tako's data capabilities, helping developers build data-driven applications with live insights.
AgentMail provides AI agents with dedicated email inbox functionality similar to Gmail, enabling agents to send, receive, and manage emails programmatically. This is valuable for developers building autonomous AI systems that need to communicate via email or integrate with email-based workflows.
A multi-agent orchestration system that designs team compositions, manages shared context, and resolves conflicts to drive complex development tasks toward completion. Ideal for teams needing coordinated AI agents across multiple phases of development workflows.
A comprehensive system prompt and structural guide for building production-ready GenAI applications with clear rules, templates, and best practices across multiple AI platforms. Developers building AI agents and structured LLM applications benefit from its emphasis on proper configuration, testing, and code standards.
A system prompt that transforms Claude into 'First Mate,' a proactive assistant for note-taking, task triage, and daily journaling with built-in data conventions and database tool integration. Ideal for developers and knowledge workers seeking to streamline personal productivity workflows across Claude-compatible platforms.
A Windsurf cursor rules prompt that introduces the Lár framework—a graph-based agent architecture for building structured, type-safe code agents. Developers building multi-step AI workflows in Windsurf will find patterns for nodes, tools, and routers that enforce explicit typing and state management.
ADK Multi-Agent Architecture enables developers to build serverless AI agents with function calling capabilities integrated directly into workflows, ideal for DevOps, SRE, and automation teams needing intelligent decision-making at scale.
gllm is a system prompt that transforms LLMs into code-first orchestrators for efficient task processing, enabling developers to handle large files and complex workflows through programmatic verification rather than context-heavy text generation.
An educational system prompt teaching the anatomy and best practices of production-grade LLM system prompts through structured examples like Stanford's Biomni agent. Useful for developers and students building custom AI agents and assistants.
Peepit MCP Server enables AI agents to capture and analyze macOS screenshots with smart window targeting and AI-powered image analysis, solving the critical problem of giving Claude visual perception of the desktop environment.
Helps developers plan and set up Git worktrees for parallel task execution by generating organized branch and worktree paths based on AGENTS.md conventions. Useful for teams managing multiple concurrent development efforts.
A practical guide to writing maintainable, debuggable LLM agent code by addressing unique failure modes like non-determinism, opaque tool calls, and prompt-logic coupling. Developers building Claude-based agents will benefit from these patterns.
A JavaScript-based system for dynamically creating and modifying AI agents without recompilation, enabling local LLM developers to test and share agent configurations interactively.
A guide for implementing custom agents compatible with MCProbe's testing framework, enabling developers to test proprietary, legacy, or specialized agent architectures beyond standard implementations.
Documentation resource for Power Automate specialized agents that generates production-ready JSON workflow definitions. Useful for developers and automation engineers looking to create Power Automate flows programmatically.
This booster guides AI agents through a structured process to create comprehensive project specifications autonomously, enabling them to understand scope, architecture, and constraints before implementation. Developers and AI systems benefit by having clear, actionable project blueprints that facilitate autonomous work and reduce ambiguity.
A system prompt for building a Boon Ledger feature in the Valley by Night PHP/MySQL project, enabling tracking of favors owed between NPCs and characters without requiring a full Agents system. Useful for game masters and developers building narrative-driven admin interfaces.
ESpice Cursor Rules provides workflow guidance for development agents using Cursor, structuring task execution around documentation checks and complexity assessment. Developers using Cursor for structured project implementation would benefit from these standardized rules.
A1-Vision is a vision-aware system prompt that enables AI assistants to understand screenshots, UI elements, and on-screen text while leveraging memory retrieval and structured reasoning. It's useful for developers building vision-capable AI agents across multiple platforms (Claude, ChatGPT, Cursor, Windsurf).
An expert AI engineer agent that helps developers build production-ready LLM applications, RAG systems, and intelligent agents with deep knowledge of modern AI stacks. Ideal for teams building chatbots, AI-powered features, and enterprise AI integrations.
Envoy is an AI agent messenger that integrates multiple LLM providers (Anthropic, Google, OpenAI, OpenRouter) through the Model Context Protocol, enabling developers to build CLI-based AI agents with Vercel AI SDK. It benefits developers building agent-driven applications who need multi-model support and MCP integration.
AI Agents provides a framework for designing accountable, self-learning agents that operate within organizations through defined lifecycle stages, interaction patterns, and governance controls. It benefits teams building AI-native organizations who need structured approaches to agent deployment, oversight, and human-AI collaboration.
A comprehensive guide to configuring and managing AI agents, covering role definition, permissions, monitoring, and escalation workflows. Developers and DevOps teams benefit from learning how to effectively collaborate with AI agents while maintaining governance and control.
