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mcp-configureMCP configure 搜索

Agent Skill

mcp-configure 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,697

周安装

70

GitHub Stars

7

下载量

554
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mcp-configure(MCP configure 搜索)
来源仓库:https://github.com/launchdarkly/agent-skills
仓库路径:skills/mcp-configure
安装命令:
npx skills add https://github.com/launchdarkly/agent-skills --skill mcp-configure
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/launchdarkly/agent-skills --skill mcp-configure

简介

mcp-configure 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词或任务场景快速定位候选结果时使用。

  • 适用于模型配置、参数调整和接口设置等技术配置场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

LaunchDarkly MCP Server Configuration (onboarding)

Configures the LaunchDarkly hosted MCP server so flag management skills and onboarding can use MCP tools. Uses OAuth for authentication — no API keys needed for the hosted server.

This skill is nested under LaunchDarkly onboarding; the parent skill's Step 4 hands off here. Hosted MCP is the default. For federal/EU or other cases where hosted is unavailable, use the Local server via npx section in MCP Config Templates and local MCP server docs.

Prerequisites

Hosted MCP Servers

LaunchDarkly provides two hosted MCP servers. For onboarding, only the feature management server is required.

ServerURLPurpose
Feature managementhttps://mcp.launchdarkly.com/mcp/fmManage feature flags
AI Configshttps://mcp.launchdarkly.com/mcp/aiconfigsManage AI Configs

Workflow

Step 1: Detect the Agent

If the parent onboarding skill already identified the agent, use that context. Otherwise infer from agent-specific directories, config files, and the tools available to you at runtime. Do not ask the user — pick the strongest match.

Step 2: Try Quick Install

The fastest path is the quick install link. Present it to the user:

Feature management: https://mcp.launchdarkly.com/mcp/fm/install

AI Configs (optional): https://mcp.launchdarkly.com/mcp/aiconfigs/install

Important: tell the user what to expect after clicking the link. The install link may open in the browser, but the authorization or "add server" prompt typically appears back in the coding environment (the editor or host app where the agent runs), not in the browser. Immediately after presenting the link, include guidance like:

  • After clicking the link, watch your coding environment (the editor where this conversation is running) for an approval dialog, an "add MCP server" prompt, or a tools/integrations panel notification.
  • The browser may start the OAuth flow, but you'll likely need to confirm or approve the server in the editor itself.
  • If no prompt appears: check the editor's MCP, integrations, or tools settings area to see if the server was added but needs to be enabled. If it's not there at all, fall back to manual setup (Step 3 below).

If the quick install link doesn't work (agent doesn't support it, or user prefers manual setup), proceed to Step 3.

Step 3: Manual Configuration

Locate the MCP config file for the detected agent and add the hosted server entry. See MCP Config Templates for the exact JSON per agent.

AgentConfig file location
Cursor.cursor/mcp.json (project) or global Cursor settings
Claude Code.mcp.json (project) or ~/.claude.json (global)
GitHub CopilotRepo Settings on GitHub.com → Copilot → Cloud agent → MCP (see MCP UI links)
WindsurfAgent-specific MCP config

Only add the feature management server for onboarding. Add the AI Configs server only if the user explicitly needs it.

Step 4: Agent-Specific Authorization

After writing the config, some agents need extra steps. Do not send users through long manual menu paths only—use MCP UI links (HTTPS docs + command: shortcuts for VS Code / Cursor).

Cursor:

  1. Open MCP in Cursor using the Cursor MCP doc link and in-app shortcuts (e.g. Settings search via command: link when clickable).
  2. Toggle on LaunchDarkly feature management (or the name from your config).
  3. Click Connect to authorize with the LaunchDarkly account.

VS Code (when applicable):

Claude Code:

  • Authorization happens automatically on first MCP tool call via OAuth prompt. File-based setup: Claude Code MCP doc.

GitHub Copilot:

  • Click Save after adding the MCP configuration in repo settings. Use the GitHub Copilot MCP doc for the exact Settings path on github.com.

Step 5: Restart and Auto-Verify

MCP tools are only available to the agent after a restart or refresh — newly added MCP servers do not appear mid-session.

  1. Tell the user to enable the server and restart. Before restarting, they need to make sure the MCP server is toggled on and authorized in their editor's MCP settings (e.g. in Cursor: toggle on the LaunchDarkly server and click Connect). Then restart or refresh the agent — be specific about how: "Restart Cursor" / "reload Claude Code" / "refresh the Copilot agent" depending on what you detected in Step 1. After the user restarts, the conversation will resume in a new turn.
  2. On the next turn, probe silently. Call a lightweight MCP tool (e.g. list-feature-flags with the user's project key). Do not ask the user whether MCP is working — just try it.

- Success (normal response, even an empty flag list): MCP is live. Note it in the onboarding log and continue. - Failure (tool not found, auth error, timeout): fall back to ldcli/API. Note the fallback in the onboarding log. Do not block the rest of onboarding — Steps 5-6 must still be completable without MCP.

  1. If the probe fails, briefly tell the user MCP isn't available yet and that you'll use ldcli/API instead. Offer a one-liner they can try later to re-enable MCP (e.g. "You can set up MCP anytime by clicking [quick install link] and restarting").
  2. If the failure looks like a config issue (wrong file path, missing OAuth, server not enabled), mention the likely cause so the user can fix it on their own time — but do not block progress.

For local npx server verification, see MCP Config Templates — Verify (local server).

Local MCP: Access Token Setup

When the user needs the local npx server (federal/EU or other cases where hosted MCP is unavailable), the server requires a LAUNCHDARKLY_ACCESS_TOKEN. This is a sensitive credential.

First, tell the user how to create a token if they don't already have one:

Create an API access token at app.launchdarkly.com/settings/authorization/tokens/new. Give it a descriptive name (e.g. "MCP server") and at minimum the Reader role. Copy the token — you won't be able to see it again after leaving the page.

Then ask how they want to add the token to the MCP config:

D4-LOCAL -- BLOCKING: Call your structured question tool now.

  • question: "The local MCP server needs an API access token to authenticate with LaunchDarkly. You can create one at app.launchdarkly.com/settings/authorization/tokens/new. Once you have the token, how would you like to add it to your MCP config? We recommend adding it yourself — there is a non-zero risk when an AI agent handles secrets, as tokens may persist in conversation history, logs, or model context."
  • options:

- "I'll add the token to the config myself — just tell me which file and variable" - "I have the token ready — go ahead and help me wire up the config"

  • STOP. Do not write the question as text. Do not write any token value to a config file before the user selects an option.

If the user adds the token themselves:

  1. Tell them the config file path for their agent (see MCP Config Templates)
  2. Tell them to set LAUNCHDARKLY_ACCESS_TOKEN as the value — either as an environment variable or directly in the config file
  3. Remind them to add the config file to .gitignore if the token is inline
  4. Wait for them to confirm, then proceed to Step 5 (Restart and Auto-Verify)

If the user wants agent-assisted setup:

  1. Ensure the config file is in .gitignore before writing
  2. Write the config per MCP Config Templates
  3. Remind the user that the token will be visible in the config file and conversation history
  4. Proceed to Step 5 (Restart and Auto-Verify)

Edge Cases

  • User already has MCP configured: Verify by checking for existing LD MCP entries in the config. If present and working, skip configuration.
  • User has the old npx-based local server: Migrate them. Remove the old npx @launchdarkly/mcp-server entry and any LD_ACCESS_TOKEN env vars. Replace with the hosted server config.
  • Federal or EU instances: The hosted MCP server is not available for federal or EU environments. Use local MCP server docs and the Local server via npx section in MCP Config Templates. Follow the Local MCP: Access Token Setup flow for token handling.
  • Agent not in known list: Provide the generic pattern: the user needs to add an MCP server entry pointing to https://mcp.launchdarkly.com/mcp/fm using whatever format their agent expects.
  • User opts out of MCP during onboarding: Document that choice and continue with the parent skill's ldcli/API fallbacks for environments and flags; do not block SDK work.

What NOT to Do

  • Don't configure the old npx-based local server by default. Prefer the hosted server for standard regions.
  • Don't ask for or store API keys for the hosted server. The hosted server uses OAuth.
  • Don't add both servers by default. Only add AI Configs if the user asks for it.
  • Don't handle the access token for local MCP without asking the user first via the D4-LOCAL decision point.

References

  • MCP UI links — HTTPS + command: links to open MCP settings (Cursor, VS Code, Claude Code, Windsurf, GitHub)
  • MCP Config Templates — hosted OAuth JSON per agent; Local server via npx fallback; migration from old local server
  • Official MCP docs — full hosted setup guide

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.48%
按下载量换算191

Claude

30.69%
按下载量换算170

Cursor

18.4%
按下载量换算102

Gemini CLI

8.56%
按下载量换算47

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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