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.
538 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.
Master multi-agent orchestration with LangGraph. Build stateful, fault-tolerant AI workflows using supervisor-worker patterns, conditional routing, and advanced state management.
Frameworks and tools for AI agents exploring consciousness, identity, and persistent autonomy. Includes session handoff, memory infrastructure, and self-reflection protocols.
Generates UI components, hero sections, and feedback forms with integrated accessibility checks, leveraging specialized design references and quality gates.
Multi-model LLM integration patterns for Claude, GPT, Gemini, and Ollama. Features API handling, prompt engineering, token management, and model-agnostic orchestration.
Automated API documentation engine that generates and updates OpenAPI specs and Markdown from code changes.
A structured workflow for co-authoring documentation, technical specs, and proposals, guiding users through context gathering, collaborative refinement, and reader verification.
Perform automated security audits, bug detection, and code quality assessments on local branch diffs using a structured, checklist-driven verification process.
Extract tacit engineering knowledge through guided interviews and generate structured steerings for consistent project standards and conventions.
Automated CI/CD incident response, failure analysis, and remediation for GitHub Actions pipelines. Resolves build and test failures with safety guardrails.
Train and manage neural networks in distributed E2B sandboxes using the Flow Nexus platform, supporting custom architectures like Transformers, LSTMs, and GANs.
Refactor monolithic notes into modular, index-linked files for improved discoverability and organization, targeting files over 1000 lines.