「mcp」の検索結果

Open the Cross-Code Organizer (CCO) dashboard — view and manage all memories, skills, MCP servers, hooks, and configs across scopes

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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.

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Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface: 6 tools with --full (adds check_action); 13 tools with AR_EXTRAS=1 --full. 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.

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Provides SonarQube and SonarCloud integration patterns via the Model Context Protocol (MCP) server. Enables quality gate monitoring, issue discovery and triaging, pre-push code analysis, and rule education directly in the agent workflow. Use when the user wants to check quality gates, search for Sonar issues, analyze code snippets before committing, or understand SonarQube rules. Triggers on "sonarqube", "sonarcloud", "quality gate", "sonar issues", "analyze with sonar", "check sonar", "sonar rule", "pre-push analysis".

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-agent-camp用のCodexツーリングを設定するスキル。 「MCPサーバーを設定」「フックをインストール」「Codexの設定」「ツールセットアップ」「Codex CLIのインストール」等のリクエストで発動。

Connect and verify the Well MCP — authenticate, confirm the tools work, and show what to ask. Use when the user runs /well:connect, just installed the Well plugin, or says the Well connection/MCP "isn't working" / "nothing happened".

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Guide for creating new MCP server integrations

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Converts documents and URLs to markdown via tiered fallback (MCP markitdown, native tools, user notice). Use when a skill must ingest PDF, DOCX, or URL content.

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。

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

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 XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state, capture logs/console output, or diagnose runtime behavior using XcodeBuildMCP tools.

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MCP server attack hunting - tool poisoning, indirect prompt injection via tool output, rug-pull updates, cross-tool shadowing, over-permissioned/excessive-agency tools, lethal trifecta. Wiki-first, FIND schema output.

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Use when exposing Spring Boot 3 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 1.x tool callback registration, transports, schemas, errors, security, and standalone MCP Java SDK compatibility.

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Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

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Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.

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 when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.

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。

Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.

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Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.

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Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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Publishes a local Markdown file to a user-specified Confluence location, creating a new page or updating an existing one through the Atlassian MCP server. Use when the user wants to post, publish, push, or sync a Markdown file to a Confluence space or page. Requires a configured Atlassian MCP server. Does not write or generate the Markdown itself — point it at an existing file, or use project-documentation-to-confluence for the document-then-publish flow, or plan-a-feature-to-confluence for the plan-then-publish flow. Does not publish to Jira — use work-items-to-jira.

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Use when writing, testing, or preparing ANY contribution or pull request to the JSONbored/awesome-claude (HeyClaude) repo — adding a community content entry (agent/MCP server/skill/hook/command/rule/guide/collection/statusline), or making a platform/code change (website, registry package, MCP package, scripts). The repo has two separate review paths: a private, one-shot "HeyClaude submission gate" that decides single-file content PRs, and the shared gittensory-orb bot that posts an advisory readiness/linked-issue comment on platform/code PRs but does not itself merge or close content PRs. Unlike JSONbored/gittensory and JSONbored/metagraphed, a linked issue is OPTIONAL here — do not import their mandatory-linked-issue rule into this repo. Invoke for any "contribute to / open a PR against / submit an entry to / fix a bug in awesome-claude (HeyClaude)" task.

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。

Scan code, dependencies, containers, IaC and SBOMs with Snyk via its first-party MCP server: authenticate, trust a folder, run the right scanner, read the findings, fix and re-scan. Includes package-health checks before adding a dependency.

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 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。

Diagnose malformed calls, retries, and unusable results after an agent selects an MCP tool.

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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。