Back to Skills

context-a8c-mcporter

majiayu000
Updated Today
1 views
58
9
58
View on GitHub
Metamcpautomationdesign

About

This Claude Skill enables querying Automattic's internal systems like Linear, Slack, and Zendesk via the `mcporter` CLI. It uses a two-step pattern: first discover and load a provider, then execute queries against it. Use this skill when answering questions about internal issues, messages, tickets, or build systems.

Quick Install

Claude Code

Recommended
Plugin CommandRecommended
/plugin add https://github.com/majiayu000/claude-skill-registry
Git CloneAlternative
git clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/context-a8c-mcporter

Copy and paste this command in Claude Code to install this skill

Documentation

Context A8C via mcporter

Access Automattic work context using mcporter CLI.

Discovery

First, discover available providers and their descriptions:

mcporter list context-a8c

This returns the full tool schema including:

  • Available providers (in the provider enum)
  • What each provider does (in the description)
  • Required and optional parameters

Read this output carefully - it tells you exactly which providers exist and when to use each one.

Two-Step Pattern

Context-a8c uses a load-then-execute pattern:

Step 1: Load Provider

mcporter call context-a8c.context-a8c-load-provider provider=<provider>

This returns the available tools for that provider and their parameters.

Step 2: Execute Tool

mcporter call 'context-a8c.context-a8c-execute-tool(provider: "linear", tool: "issue", params: {"id":"SQUARE-215"})'

Params are optional; omit params entirely for tools without arguments:

mcporter call 'context-a8c.context-a8c-execute-tool(provider: "linear", tool: "me")'

The params argument must be an object (not a JSON string). Wrap the whole call in single quotes to avoid shell parsing issues.

Workflow

  1. Run mcporter list context-a8c to see available providers
  2. Load the relevant provider to discover its tools
  3. Execute the specific tool with appropriate params
  4. Parse JSON results

End-to-End Example (Linear Issue)

mcporter list context-a8c
mcporter call context-a8c.context-a8c-load-provider provider=linear
mcporter call 'context-a8c.context-a8c-execute-tool(provider: "linear", tool: "issue", params: {"id":"SQUARE-215"})'

Common Errors

  • tool is a required property of input → include tool: "<tool>" in the execute call.
  • provider is a required property of input → include provider: "<provider>" in the execute call.
  • input[params] is not of type object → pass an object, not a quoted JSON string.

Notes

  • Always load a provider first to see exact tool names and parameters
  • The params argument must be valid JSON when provided
  • Auth is handled automatically; if it fails, direct user to /ai/context-a8c on Matticspace

GitHub Repository

majiayu000/claude-skill-registry
Path: skills/context-a8c-mcporter

Related Skills

content-collections

Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill

creating-opencode-plugins

Meta

This skill provides the structure and API specifications for creating OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It offers implementation patterns for JavaScript/TypeScript modules that intercept and extend the AI assistant's lifecycle. Use it when you need to build event-driven plugins for monitoring, custom handling, or extending OpenCode's capabilities.

View skill

sglang

Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill

langchain

Meta

LangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.

View skill