Packs

12 packs

Create MCP Server in TypeScript

Generate a complete MCP server project with tools, resources, and proper configuration.

7 skills · pack

Generate MCP Server in Python

Generate a complete MCP server project in Python with tools, resources, and proper configuration using uv and the MCP SDK.

9 skills · pack

Build agents, MCP servers and tool-using workflows.

34 skills · pack

@mariadb-corporation

MariaDB skills + the native mariadb-shell MCP server.

75 skills · pack

Adobe Analytics

Practitioner skills for Adobe Analytics via the AA MCP server

5 skills · pack

Practitioner skills for Adobe Customer Journey Analytics via the CJA MCP server

6 skills · pack

MCP Security Audit Pipeline

Audit MCP servers for secrets exposure, shell injection, and supply chain risks.

12 skills · pack

Azure Database Management

For .NET developers managing Azure PostgreSQL and MySQL Flexible Server deployments with the Azure SDK.

6 skills · pack

Deploy AI Inference on GKE

Deploy and optimize AI/ML inference workloads on GKE using GPUs, TPUs, and model servers.

3 skills · pack

A comprehensive example plugin demonstrating all Claude Code extension options including commands, agents, skills, hooks, and MCP servers

2 skills · pack

Simulator.Company platform assistant. Exposes the Simulator REST API as an MCP server and provides skills for managing actors, forms, graph structures, and financial accounts.

19 skills · pack

Redpanda Data Skills

Agent Skills for Redpanda's five products — Streaming (Kafka-compatible engine), SQL (Oxla), Connect (incl. CDC connectors), Cloud (Serverless, BYOC, Dedicated), and the Agentic Data Plane — plus the rpk CLI. Grounded in Redpanda source, docs, and APIs.

32 skills · pack

Results for “server”

11 skills

orchestra-research

modal-serverless-gpu

Run ML workloads on Modal's serverless GPU cloud platform with auto-scaling, pay-per-second pricing, and Python-native infrastructure.

10.4k · bundle

modal-serverless-gpu

Run ML workloads on Modal's serverless GPU cloud: deploy models as auto-scaling APIs, run batch jobs, and schedule tasks with pay-per-second GPU pricing.

Deploy and serve AI/ML models on Modal's serverless cloud platform with on-demand GPUs, autoscaling containers, persistent storage, and scheduled jobs.

30.2k · bundle

huggingface-local-models

Search the Hugging Face Hub for llama.cpp-compatible GGUF models, select the right quantization, and run them locally with llama-cli or llama-server.

10.8k · bundle

hf-cloud-sagemaker-deployment-planner

Plans and coordinates the deployment of a model to Amazon SageMaker AI, selecting the appropriate pathway (real-time, serverless, async, batch, or Bedrock CMI) based on model type, traffic, latency, and cost constraints.

More results

nemo-evaluator-plugin

Run evaluation tasks against a NeMo Platform server using the Evaluator plugin CLI and Python SDK.

Run GGUF models locally with llama.cpp, including finding the right file on the Hugging Face Hub, installing, quantizing, serving, and using Python bindings.

jetson-speculative-decoding

Reduce per-token latency on Jetson vLLM servers by appending speculative decoding configuration, with guidance on when to enable and how to benchmark the improvement.

Search models, datasets, Spaces, and papers on Hugging Face Hub, retrieve repository details and documentation, run compute jobs, and use Gradio Spaces as AI tools via MCP server tools.

Connects AI assistants to the Hugging Face Hub via MCP server tools to search models, datasets, Spaces, and papers, retrieve repo details and documentation, run compute jobs, and use Gradio Spaces as AI tools.

Connects AI assistants to the Hugging Face Hub via MCP server tools to search models, datasets, Spaces, and papers, retrieve repository details and documentation, run compute jobs, and use Gradio Spaces as AI tools.