623 boosters for "agent" — AI-graded, open source, ready to install
MCP Server that enables AI agents to analyze and auto-optimize Linux kernel schedulers using eBPF, helping systems engineers improve performance through intelligent workload profiling and optimization strategies.
rtfmbro-mcp provides AI coding agents with always-up-to-date, version-specific package documentation to prevent outdated knowledge errors. Developers and teams using Claude/Copilot for agentic coding tasks benefit from accurate, real-time API references.
An MCP server that enables Claude to maintain persistent long-term and short-term memory across conversations using a local SQLite database. Developers and AI agents benefit from enhanced context retention and conversation continuity.
Superargs is an MCP server that enables dynamic runtime updates to MCP server arguments and environment variables without restarts. It's useful for developers building flexible AI agent systems that need to adapt configuration on-the-fly.
A comprehensive guide for creating and managing autonomous agents within the CrewAI framework, enabling developers to build specialized AI team members with defined roles, goals, and collaborative capabilities. Ideal for developers building multi-agent AI systems who need clear patterns for agent design and configuration.
An MCP server that integrates ERPNext ERP systems with Claude AI, enabling AI agents to interact with business data and workflows. Useful for developers and businesses automating ERPNext operations through Claude.
A Copilot integration that adds AI-powered chat assistance to Redmine project management, enabling developers to interact with issues, repositories, wikis, and other Redmine features through a multi-agent architecture. Developers and Redmine administrators benefit from streamlined task automation and intelligent issue handling.
This skill parses natural language shopping queries to extract structured search criteria like product type, attributes, price limits, and specifications. E-commerce AI agents and developers building shopping assistants benefit from this structured approach to query understanding.
Concurrent Sub-Agents is an agentic terminal application that enables multi-agent workflows by automatically executing independent sub-agent tool calls in parallel, reducing latency without requiring explicit concurrency logic from the LLM. Developers building complex AI agent systems on Claude will benefit from faster, more efficient agent coordination.
Turkey-build is a multi-agent orchestration system for building production-ready applications across 7 modes (greenfield, iteration, bugfix, refactor, UI polish, migration, audit), with PM-driven coordination and runtime verification for teams that need structured, quality-gated development workflows.
Interactive Agents enables multi-level agent communication through a stack-based model where subagents take over conversation threads interactively until completion. Developers building complex agent systems with nested tool calls and dynamic routing will benefit from this orchestration pattern.
atris is a self-improving context system that provides structured agent rules and workflows for AI coding assistants like Cursor, enabling developers to maintain organized task management, code navigation, and communication standards across projects.
Luca is an AI agent that automates the creation of invoices, quotations, and receipts by gathering user information, generating JSON specifications, producing PDF documents, and drafting professional client emails. It's ideal for freelancers and small business owners who need to streamline financial document workflows.
Windsurf Rules for agenterra establishes mandatory instructions and workflows for AI agent development, including PR practices and test-driven development standards. It benefits developers working with the agenterra agent framework who need consistent operational guidelines.
A Copilot-optimized guide for AI agents working in a full-stack NestJS/Next.js monorepo SaaS boilerplate, providing structured commands, code standards, and project architecture for efficient development.
gomcp provides a Go implementation of the Model Context Protocol to enable AI agents in Cursor to interact with external tools and resources through a standardized interface. Developers using Cursor who need to extend AI capabilities with custom integrations benefit from this protocol implementation.
An MCP server that integrates Crawlbase API for web scraping capabilities into AI agents and code editors like Claude, Cursor, and Windsurf. Developers building AI applications needing reliable web data extraction benefit from this seamless integration.
A comprehensive guide for developers adding new agents to Errata, a writing application. Useful for backend engineers extending LLM-powered features like character optimization and prose analysis.
StarkBot is a system prompt that enables an AI agent to respond via structured JSON and call tools across multiple IDE platforms (Claude, Cursor, Windsurf, ChatGPT). It's useful for developers building tool-integrated AI workflows in code editors.
Syncs OpenClaw framework, ClawHub, and Skills documentation into a local searchable mirror for the QMD memory backend, enabling AI agents to access fresh, precise references during coding tasks.
Cursor rules for implementing Agency Swarm with Mem0 memory management, enabling developers to build collaborative multi-agent systems with persistent memory capabilities.
A layered backend architecture ruleset for Go/TypeScript projects that enforces clean dependency patterns (core → infra → database/permission → server) to maintain code organization and testability in internal tools. Ideal for teams building admin dashboards and CRUD applications who need consistent architectural guidance.
This MCP server enables AI coding agents to analyze test coverage from LCOV files, making them coverage-aware while optimizing token usage. It's valuable for developers using Claude Desktop or Code who want to improve code quality by integrating coverage insights into their AI-assisted workflows.
Recall automatically searches across memory sources when users make vague references to past conversations, helping an AI assistant reconstruct context without guessing. Ideal for users who frequently reference earlier discussions and need reliable context retrieval.
