「mcp」の検索結果

Investigate MCP tool availability, discovery, and selection, including controlled adoption evaluations.

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。

Investigate a Rezolus performance recording (.parquet, .rez, .dendro) through the rezolus MCP server. Discovery before query, verdicts and marks written back, links to the viewer.

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。

Social Media Publisher. Takes approved content from outputs/ and schedules it across platforms via Blotato MCP. Generates infographic-style visuals (stat cards, framework diagrams, process graphics, quote graphics) for posts flagged by platform-specialist skills. Requires Blotato MCP to be configured. Run after /linkedin-writer, /threads-writer, /x-writer, or /caption-writer.

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。

Build TestDriver tests iteratively using MCP tools with visual feedback

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。

claude-mcp-plugin

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。

麦当劳门店派对/包场/拼团的选址、成团调度与筹备助手。当用户想办生日派对、亲子派对、主题派对、品鉴会、读书会、麦麦体验营，或说「麦当劳派对」「派对拼团」「包场」「生日会怎么办」「哪家店能办派对」「还差几个人成团」「包场还是拼团划算」「帮我写拼团招募文案」「做一张派对邀请函」「孩子派对吃什么不超标」时使用。基于麦当劳官方 MCP（mcp.mcd.cn）的 party 系列工具：扫描全城场次、估算成团概率、对比包场与拼团成本、按官方营销活动日历挑最佳日期、审查儿童餐营养、生成招募卡与邀请函。

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。

Expert SurrealDB 3 architect and developer skill (tracks v3.1.4+). SurrealQL mastery, multi-model data modeling (document, graph, vector, time-series, geospatial), schema design, security, deployment, performance tuning, SDK integration (JS, Python, Go, Rust, Java, .NET, C, PHP, Swift, Kotlin, Ruby), Surrealism WASM extensions, SurrealML scope coverage (preview), built-in MCP (v3.1+) and standalone SurrealMCP, LangChain Python integration, editor tooling (LSP v0.1.6, tree-sitter, CodeMirror v1.0.6, VS Code/JetBrains/Neovim/Zed), and ecosystem integrations (Surrealist v3.9, Surreal-Sync, SurrealFS, SurrealKit v0.7, n8n, Agent Skills, setup-surreal). Universal skill for 30+ AI agents.

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。

Connects Claude Code, Codex, Cursor, and other MCP hosts to Writingmate for model discovery, text comparison, image generation, and video generation with Seedance, Sora, Veo, Kling, PixVerse, and other available models.

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。

IOTA blockchain MCP server providing wallet management with human-in-the-loop signing, Move smart contract build/test/publish, and on-chain queries via JSON-RPC and GraphQL. Use when interacting with IOTA network from AI coding agents, managing IOTA wallets, building or publishing Move packages, querying on-chain objects or transactions, or checking epoch and network statistics.

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。

Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface (18 tools) available with --full flag. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.

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。

Import Figma content into a HyperFrames composition — rendered assets, brand tokens, components, storyboard sections → reconstructed motion (frames read as states, not slides) (REST/CLI), Figma Motion animations (MCP), and shaders (MCP source / native export). Use when the user pastes a figma.com link or asks to bring a Figma design, frame, logo, brand, or animation into a video/composition.

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。

Ultimate MCP server for Civitai — search models, browse top images with prompts, download LoRAs/Checkpoints, analyze trends. Use when user asks about AI models, LoRAs, checkpoints, Stable Diffusion, Flux, image generation prompts, or Civitai.

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。

Build MCP (Model Context Protocol) servers on Cloudflare Workers with tools, resources, and prompts.

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。

思源任务笔记管理插件 MCP 工具总览技能。

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。

Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).

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。

Goal-driven E2E testing where a browser agent (Playwright MCP / computer-use) reads a natural-language goal and explores the app via the accessibility tree to assert outcomes — no pre-written script. Covers when intent-driven beats scripted, making agent runs deterministic (pinned model, temperature 0, seeded data, bounded steps, explicit success assertion, snapshot-not-pixel), cost/latency control, the accessibility-tree-first interaction model, CI gating, and graduating a stable run into a scripted Playwright test. Use when: "agentic browser test," "goal-driven browser test," "let an agent explore the app," "natural-language E2E," "browser agent smoke test," "Playwright MCP test." Not for: Writing/maintaining deterministic scripted Playwright tests — that is playwright-automation. Testing your product's OWN LLM features — that is ai-system-testing. Related: playwright-automation, ai-system-testing, exploratory-testing, test-reliability, qa-project-context.

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。

Build software with Cursor, the AI-powered code editor. Use when a user asks to configure Cursor rules, set up .cursorrules files, use Composer for multi-file edits, integrate MCP servers, or optimize AI-assisted coding workflows.

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。

Context7 fetches current, version-specific documentation and code examples for software libraries and hands them to an AI coding agent, so generated code matches the library version in use instead of stale training data. Use when someone says "use context7", "get the latest docs for this library", "look up the current API", "the agent keeps using a deprecated method", "set up Context7 in Claude Code or Cursor", or asks how to call a framework whose API changed recently. Covers the ctx7 CLI, the MCP server and its two tools, library IDs and version pinning, API keys and rate limits, and the REST API.

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 Memory Skill workflow skill. Use this skill when the user needs A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions) and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

AI image generation and editing for blog content powered by Gemini via MCP. Claude acts as Creative Director - interpreting intent, selecting domain expertise, constructing optimized 6-component prompts (Subject + Action + Context + Composition + Lighting + Style), and orchestrating Gemini for blog-quality results. Generates hero images, inline illustrations, social preview cards, and OG images. Edits existing blog images. Supports 6 blog-optimized domain modes (Editorial, Product, Landscape, UI/Web, Infographic, Abstract). Works standalone via /blog image or internally from blog-write and blog-rewrite workflows. Falls back gracefully when MCP is not configured. Use when user says "blog image", "generate hero image", "blog illustration", "social card", "generate blog image", "edit blog image", "image generate", "blog cover image", "inline image", "OG image".

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。

MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.

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。

Diagnose a running AionUi installation: inspect stuck or errored conversations, read provider health, scheduled task state, MCP server health, team member state, backend health, and aioncore logs. Use when the user reports AionUi is misbehaving, a conversation is stuck, an LLM/provider call is failing, a scheduled task did not run, an MCP server has no tools, a team member is hung, or they ask to troubleshoot AionUi.

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。

Edit, trim, cut, caption, subtitle, reframe, combine, add background music to, or export video, audio, and image files through Cassette. Use this skill whenever the user asks to change, preview, or render a media file in the project — even if they never say "Cassette" or name a tool — for example "trim the intro off demo.mp4", "add subtitles to this clip", "make me a 30-second cut with music", "why is there dead air at the start". Drives the local Oh My Cassette stdio MCP tools in Codex or Claude as one multi-turn conversation with the Cassette agent, with per-turn timeline previews, guided questions, and rendering only on explicit export.

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。

Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.

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。