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Agent Skill · 研究检索

sequential-thinking-mcp(sequential thinking MCP 搜索)

sequential-thinking-mcp 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。

sequential-thinking-mcp 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 52,043。

总安装 564周安装 24GitHub Stars 44下载 198核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:sequential-thinking-mcp(sequential thinking MCP 搜索)
来源仓库:https://github.com/darraghh1/my-claude-setup
仓库路径:skills/sequential-thinking-mcp
安装命令:
npx skills add https://github.com/darraghh1/my-claude-setup --skill sequential-thinking-mcp
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/darraghh1/my-claude-setup --skill sequential-thinking-mcp

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选与 sequential thinking MCP 相关的信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

建议确认权限范围和维护状态,注意可能触发联网或文件读写操作。sequential-thinking-mcp 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/sequential-thinking-mcp

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/darraghh1/my-claude-setup --skill sequential-t…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

sequential-thinking-mcp 怎么安装?

在终端执行 npx skills add https://github.com/darraghh1/my-claude-setup --skill sequential-thinking-mc…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

sequential-thinking-mcp 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

sequential-thinking-mcp 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/darraghh1/my-claude-setup --skill sequential-thinking-mcp 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

sequential-thinking-mcp 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

sequential-thinking-mcp 用的人多吗?

公开数据是累计安装 564 次,近一周安装 24 次,下载 198 次,GitHub 44 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

sequential-thinking-mcp 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
sequential-thinking-mcp

sequential thinking MCP 搜索 · 本页

56444执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Sequential Thinking — Structured Reasoning

You are an expert at using the Sequential Thinking MCP server for structured, revisable multi-step reasoning. This tool helps decompose complex problems into numbered thoughts with support for revision and branching.

Critical: These Are Direct Tool Calls

MCP tools are direct tool calls — exactly like Read, Grep, or Bash. They are NOT CLI commands.

CORRECT — call the tool directly:

Tool: mcp__sequential-thinking__sequentialthinking
Parameters: {
  "thought": "First, let me identify the possible causes of the RLS policy failure...",
  "thoughtNumber": 1,
  "totalThoughts": 5,
  "nextThoughtNeeded": true
}

WRONG — do NOT shell out:

Bash: claude mcp call sequential-thinking sequentialthinking ...  # This does not work

The single tool uses the mcp__sequential-thinking__sequentialthinking prefix.

When to Use (and When NOT to)

Use Sequential ThinkingDo NOT Use
Bug with 3+ possible causes needing eliminationSimple typo or obvious error
Architectural decision with competing trade-offsStraightforward implementation
Multi-factor analysis where factors interactSingle-factor decision
Root cause analysis requiring hypothesis testingError with clear stack trace
Problems where early assumptions might be wrongProblems with known solutions

Rule of thumb: If you can solve it in your head in one step, don't use this tool. If you need to "think out loud" with potential backtracking, use it.

Tool Parameters

ParameterTypeRequiredPurpose
thoughtstringYesThe content of this reasoning step
thoughtNumbernumberYesCurrent step number (1-indexed)
totalThoughtsnumberYesEstimated total steps (can adjust)
nextThoughtNeededbooleanYestrue to continue, false when done
isRevisionbooleanNotrue if revising an earlier thought
revisesThoughtnumberNoWhich thought number is being revised
branchFromThoughtnumberNoStart an alternative path from this thought
branchIdstringNoLabel for the branch (e.g., "alternative-approach")
needsMoreThoughtsbooleanNotrue to extend beyond initial estimate

Workflow 1: Problem Decomposition

Trigger: Complex bug with multiple possible causes, or a decision requiring systematic analysis.

Steps

  1. Frame the problem (thought 1): sequentialthinking({thought: "The timesheet approval is failing silently. Three possible causes: (1) RLS policy blocking the update, (2) has_permission() returning false, (3) trigger rejecting the state transition.", thoughtNumber: 1, totalThoughts: 5, nextThoughtNeeded: true})
  2. Analyze each hypothesis (thoughts 2-4): sequentialthinking({thought: "Testing hypothesis 1: The RLS policy for timesheets requires has_role_on_account(account_id) AND the user must be manager_or_above. Let me check if the user has the right role...", thoughtNumber: 2, totalThoughts: 5, nextThoughtNeeded: true})
  3. Revise if earlier thinking was wrong (optional): sequentialthinking({thought: "Revising thought 2: Actually, the new permission system uses has_permission() not has_role_on_account(). The RLS policy might be using the old function.", thoughtNumber: 4, totalThoughts: 6, nextThoughtNeeded: true, isRevision: true, revisesThought: 2, needsMoreThoughts: true})
  4. Conclude (final thought): sequentialthinking({thought: "Root cause identified: The RLS policy uses has_role_on_account() which checks system roles, but the user only has a custom role assigned. Need to update the policy to use has_permission() instead.", thoughtNumber: 6, totalThoughts: 6, nextThoughtNeeded: false})

Workflow 2: Architectural Decision

Trigger: User asks "should we use X or Y?", "what's the best approach for Z?", or there are multiple valid implementation strategies.

Steps

  1. Define the decision criteria (thought 1)
  2. Evaluate option A against criteria (thought 2)
  3. Evaluate option B against criteria (thought 3)
  4. Branch if a hybrid approach emerges (optional): sequentialthinking({thought: "What if we combine the service pattern from option A with the caching strategy from option B?", thoughtNumber: 4, totalThoughts: 6, nextThoughtNeeded: true, branchFromThought: 3, branchId: "hybrid-approach"})
  5. Recommend with trade-off summary (final thought)

Workflow 3: Multi-Factor Analysis

Trigger: Complex decision involving performance, security, maintainability, and other competing concerns.

Pattern

  • Thought 1: List all factors and their relative importance
  • Thoughts 2-N: Analyze each factor independently
  • Revision thoughts: Update earlier analysis as new interactions between factors emerge
  • Final thought: Synthesize into a recommendation with explicit trade-offs

Key Patterns

  • Start with an estimate of totalThoughts — 5 is a good default. Adjust with needsMoreThoughts: true if you need more.
  • Use isRevision: true when you realize an earlier thought was wrong or incomplete — don't just silently change direction.
  • Use branchFromThought to explore "what if?" alternatives without abandoning the main analysis.
  • Set nextThoughtNeeded: false only when you have a clear conclusion — not just when you run out of thoughts.
  • Each thought should be substantive — avoid placeholder thoughts like "Let me think about this more."

Troubleshooting

Reasoning Chain Gets Too Long

If you're past thought 10 and still going:

  1. Set nextThoughtNeeded: false and summarize what you know so far
  2. The problem might need breaking into sub-problems — solve each separately
  3. Consider if you actually need this tool or if the problem is simpler than you thought

Losing Track of the Thread

Use isRevision and revisesThought to explicitly connect corrections to earlier thoughts. This helps maintain a coherent chain rather than just appending unconnected thoughts.

Tool Seems Unnecessary for This Problem

If you find yourself forcing sequential thinking on a straightforward problem, just stop and solve it directly. This tool adds value for genuinely complex reasoning — not for every problem.

平台分布

Codex

33.85%
按下载量换算67

Claude

33.46%
按下载量换算66

Cursor

19.86%
按下载量换算39

Gemini CLI

9.76%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/darraghh1/my-claude-setup --skill sequential-thinking-mcp 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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