437 boosters for "agents" — open source, verified from GitHub, ready to install
"version": "0.10.0", "description": "AI agents on autopilot - define in markdown, run on cron, CI/CD, or serverless", "license": "Apache-2.0",
Zettelkasten memory for AI agents. Markdown cards in with . npm package . Distributed as CLI + MCP server + Claude Code plugin + VS Code extension + Pi extension. Build has a known TS error ( optional dep). Ignore it — it compiles fine for distribution. If you add a new MCP tool:
This is the Go implementation of Vibes (main branch). The Python version lives on the branch.
Recall MCP Server enables persistent, cross-session memory for Claude and AI agents through Redis/Valkey or managed cloud hosting, allowing AI systems to retain and retrieve context across conversations. Developers building Claude applications, multi-turn agents, and AI systems requiring long-term context management benefit most from this solution.
Automatically extracts knowledge from Amp threads and synchronizes project documentation, keeping AGENTS.md and other docs up-to-date after epics and major work. Ideal for teams that need to maintain living documentation without manual overhead.
Execute the release automation script with auto-confirmation for Claude Code. PROJECTROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "$PWD") cd "$PROJECTROOT" && bash .claude/scripts/release.sh $ARGUMENTS --yes
"name": "digital-marketing-pro", "description": "Plan, execute, and measure digital marketing across all channels. 25 specialist agents handle strategy, SEO, paid ads, content, email, social, PR, analytics, CRO, and agency operations — with brand voice enforcement, quality evaluation, multilingual s
Cognitive architecture for AI-augmented software development. Specialized agents, structured workflows, and multi-platform deployment. Claude Code · Codex · Copilot · Cursor · Factory · Warp · Windsurf.
"name": "tensorlake", "description": "Tensorlake SDK for agent sandboxes and sandbox-native orchestration. Use when building AI agents that need sandboxed execution environments, isolated tool calls, or durable workflow orchestration.", "author": "TensorLake",
"name": "codeguard-security", "description": "Security code review skill based on Project CodeGuard's comprehensive security rules. Helps AI coding agents write secure code and prevent common vulnerabilities.", "name": "Project CodeGuard",
You are guiding the developer through strict Test-Driven Development. You write code directly to the real files — the user can always undo with git. Pause only when the user's input is needed, not at every step. 1. Determine the input type: 2. Detect the language and test framework from the project.
"description": "Run any model with an Anthropic- or OpenAI-compatible API (e.g. DeepSeek, GLM, Kimi, Qwen, MiniMax) — even your Codex subscription — as real Claude Code workflows, agent-team teammates, or one-shot subagents, driven exactly like native ones. Your main session's own auth is untouched
Heuristic scoring (no AI key configured).
You are managing the Feishu/Lark bridge daemon. User data is stored at . The skill directory is .
<summary >🌐 Language</summary> <div align="center"> <a href="https://openaitx.github.io/view.html?user=wshobson&project=agents&lang=en">English</a>
Sub-Agents enables parent agents to delegate specialized tasks to child agents with independent prompts, tools, and providers, allowing developers to build modular, hierarchical AI systems that solve complex multi-step problems.
A concurrent sub-agent executor that transparently parallelizes independent tool calls in agentic workflows, enabling faster multi-step operations without explicit LLM coordination. Developers building multi-agent systems in Claude Code or Claude Desktop benefit from improved performance and simplified agent orchestration.
Memelord is a persistent memory system for AI coding agents that uses vector search and reinforcement learning to help agents learn from past interactions. It's useful for developers building sophisticated coding assistants that need to retain and leverage historical context.
uni-cli is a unified command-line interface that enables AI agents to seamlessly interact with 25+ services (messaging, productivity, research, utilities) through a consistent pattern. Developers and AI builders benefit from simplified multi-service integration without learning individual APIs.
A local SQLite-based command-line task board for AI agents and developers to manage multi-step coding tasks, track progress, and coordinate work across sessions without external dependencies. Ideal for breaking down complex implementations into trackable subtasks with comments and checklists.
Automates GitHub issue triage and fixing by fetching issues, spawning AI sub-agents to implement solutions, opening PRs, and handling review feedback—ideal for maintainers and teams managing high-volume bug backlogs.
"name": "prism-mcp-server", "mcpName": "io.github.dcostenco/prism-mcp", "description": "The Mind Palace for AI Agents — persistent memory (SQLite/Supabase), behavioral learning & IDE rules sync, multimodal VLM image captioning, pluggable LLM providers (OpenAI/Anthropic/Gemini/Ollama), OpenTelemetry
"name": "@ticktockbent/charlotte", "description": "Token-efficient browser MCP server — structured web pages for AI agents, not raw accessibility dumps", "main": "dist/index.js",
"name": "@paretools/bazel", "version": "0.16.1", "mcpName": "io.github.Dave-London/pare-bazel",
