Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Use to build, wire up, or debug an MCP (Model Context Protocol) server that gives Claude access to an internal API, database, or SaaS tool. Trigger when the user wants Claude to connect to their own system, asks for an MCP server, needs custom tools for Claude Code or the Claude app, or an existing server's tools are not showing up.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
An MCP server is how Claude reaches a system it does not otherwise know about — your database, your internal API, your ops tooling. The protocol is small. Almost every real problem is a design problem: which tools to expose and what they return.
Local (stdio) — runs on the user's machine, launched by the client, credentials from the local environment. Right for developer tooling and anything touching localhost or a local database. Only that machine gets it.
Remote (HTTP) — deployed once, reached by URL, OAuth for identity. Right when a team needs it, or when the data lives in a service rather than on a laptop. Everyone gets updates the moment you deploy.
Build remote when more than one person will use it. Retrofitting local-only to multi-user later means redoing auth from scratch.
Tools are an interface for a model, not a REST API. The common failure is exposing twenty thin endpoint wrappers and watching the model chain them badly.
get_pipeline_board beats query_deals plus query_stages plus query_owners.execute that takes arbitrary input.Ten well-shaped tools beat fifty thin ones.
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js'
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js'
import { z } from 'zod'
const server = new McpServer({ name: 'acme-crm', version: '1.0.0' })
server.tool(
'get_deal',
'Fetch one deal with its owner, stage, and recent activity. Use when the user names a specific deal or company.',
{ id: z.string().describe('Deal id or display id like D-1042') },
async ({ id }) => ({ content: [{ type: 'text', text: await renderDeal(id) }] }),
)
await server.connect(new StdioServerTransport())
Check the SDK's current API before writing more than this — the interface has changed across releases, and code written from memory tends to target an older one.
npx @modelcontextprotocol/inspector node build/index.js # exercise tools directly
claude mcp list # is it registered
claude mcp get <name> # config and status
Tools missing in the client is nearly always one of: the server crashed on startup (run it by hand and read stderr), a stdio server wrote a stray console.log to stdout and corrupted the protocol stream, the config points at a stale build, or the client was not restarted. For stdio servers, all logging goes to stderr — stdout belongs to the protocol.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
日本語の概要は準備中です。原文の説明を表示しています。
Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
日本語の概要は準備中です。原文の説明を表示しています。
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
日本語の概要は準備中です。原文の説明を表示しています。
Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.
日本語の概要は準備中です。原文の説明を表示しています。
Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.
日本語の概要は準備中です。原文の説明を表示しています。