10 skills found
openclaw / model-usageUse CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
openclaw / lobsterLobster Lobster executes multi-step workflows with approval checkpoints. Use it when: - User wants a repeatable automation (triage, monitor, sync) - Actions need human approval before executing (s
JetBrains / koogKoog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expertise and provides proven solutions for complex LLM and AI problems
Jpisnice / shadcn-ui-mcp-serverA mcp server to allow LLMS gain context about shadcn ui component structure,usage and installation,compaitable with react,svelte 5,vue & React Native
moltis-org / moltisA Rust-native claw you can trust. One binary — sandboxed, secure, auditable. Voice, memory, MCP tools, and multi-channel access built-in.
domdomegg / airtable-mcp-server🗂️🤖 Airtable Model Context Protocol Server, for allowing AI systems to interact with your Airtable bases
Fatmike-GH / MCPDebuggerA lightweight MCP debugger designed for learning and experimentation. Supports Windows executables (x86 and x64).
jackdark425 / aigroup-mdtoword-mcpMarkdown-to-Word MCP server with advanced styling, formulas, tables, Mermaid rendering, and HTTP deployment support.
xynehq / jaf-pyFunctional Python agent framework with MCP support, enterprise security, immutable state, and production-ready observability for building scalable AI systems.
spinualexandru / humanagentprotocolA universal protocol for symbiotic collaboration between humans and autonomous AI agents. HAP enables AI agents to request human decisions in a structured, auditable, and latency-safe manner. Agents never block — they create tickets with defined timeout behaviors, allowing graceful degradation or escalation.
