hf-mcp
Connect your AI agent to the Hugging Face Hub via MCP. Search models, datasets, and papers, manage repos, run cloud compute jobs, and invoke Gradio Spaces as functional AI tools.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
261 skills found
Connect your AI agent to the Hugging Face Hub via MCP. Search models, datasets, and papers, manage repos, run cloud compute jobs, and invoke Gradio Spaces as functional AI tools.
Integrate, fix, and debug Duit/flutter_duit backend-driven UI (BDUI) in Flutter applications. Supports remote/static layouts, custom components, transport managers, and lifecycle debugging.
Initiates automated reverse engineering by discovering codebase architecture, layers, and technology stacks to facilitate system modernization or documentation.
Expert technical support for the Litestream disaster recovery tool, covering WAL monitoring, LTX replication, cloud storage backends, and SQLite page management.
Production-grade observability stack featuring Prometheus metrics, Grafana dashboarding, PromQL query language, alerting rules, and AI-powered anomaly detection for cloud-native applications.
Standardized technical documentation templates for ADRs, runbooks, architecture, and knowledge transfer in AI agent workflows.
A microworld operating system for LLM-based agent living memory, transforming filesystems into navigable rooms and code into habitable worlds.
P9 Tech Lead mode: Manages P8 agent teams via Task Prompts (six-element) without direct coding. Orchestrates 3+ parallel agents for project management, task decomposition, and architecture.
Expert guidance and configuration standards for creating specialized OpenCode AI agents, including YAML frontmatter, tool permissions, and operational modes.
Open-source infrastructure for reliable, multi-destination event delivery. Route webhooks to HTTP, SQS, RabbitMQ, Pub/Sub, EventBridge, or Kafka with built-in retries and observability.
A specification-driven workflow management system for structured development lifecycle management, covering proposal, planning, implementation, and archival phases.
Apply context-driven testing principles to adapt testing strategies based on project goals, risks, and constraints rather than relying on universal best practices.