MCP Sequential Thinking Tools
mcp-sequentialthinking-tools
MCPシーケンシャル・シンキング・サーバーを改良したもので、問題解決におけるツール活用をガイドするように設計されています。このサーバーは、複雑な問題を扱いやすいステップに分解し、各段階で最も効果的なMCPツールを推奨します。
モデルコンテキストプロトコル(MCP)サーバーは、シーケンシャルシンキングとインテリジェントなツール提案を組み合わせます。問題解決プロセスの各ステップにおいて、信頼度スコアに基づいた推奨ツールと、各ツールが適切である理由の根拠を提供します。
特徴
🤔 連続的な思考による動的かつ反省的な問題解決
🔄適応し進化する柔軟な思考プロセス
🌳 思考の分岐と修正をサポート
🛠️ 各ステップでインテリジェントなツールの推奨
📊 ツール提案の信頼度スコア
🔍 ツール推奨の詳細な根拠
📝 期待される成果を伴う歩数追跡
🔄 前のステップと残りのステップの進捗状況の監視
🎯 各ステップの代替ツールの提案
Related MCP server: Clear Thought Server
仕組み
このサーバーは、思考プロセスの各ステップを分析し、タスクの達成に役立つ適切なMCPツールを推奨します。各推奨には以下の内容が含まれます。
ツールが現在のニーズにどれだけ適合しているかを示す信頼度スコア(0~1)
ツールがなぜ役立つのかを説明する明確な根拠
ツールの実行順序を提案する優先度レベル
使用できる代替ツール
サーバーは、環境内で利用可能なあらゆるMCPツールと連携します。現在のステップの要件に基づいて推奨事項を提供しますが、実際のツール実行はコンシューマー(Claudeなど)によって処理されます。
使用例
サーバーがツールの使用をガイドする方法の例を次に示します。
{
"thought": "Initial research step to understand what universal reactivity means in Svelte 5",
"current_step": {
"step_description": "Gather initial information about Svelte 5's universal reactivity",
"expected_outcome": "Clear understanding of universal reactivity concept",
"recommended_tools": [
{
"tool_name": "search_docs",
"confidence": 0.9,
"rationale": "Search Svelte documentation for official information",
"priority": 1
},
{
"tool_name": "tavily_search",
"confidence": 0.8,
"rationale": "Get additional context from reliable sources",
"priority": 2
}
],
"next_step_conditions": [
"Verify information accuracy",
"Look for implementation details"
]
},
"thought_number": 1,
"total_thoughts": 5,
"next_thought_needed": true
}サーバーはあなたの進捗状況を追跡し、以下をサポートします。
さまざまなアプローチを探索するためのブランチの作成
新しい情報で以前の考えを修正する
複数のステップにわたってコンテキストを維持する
現在の調査結果に基づいて次のステップを提案する
構成
このサーバーはMCPクライアント経由で設定する必要があります。以下に、様々な環境における設定例を示します。
傾斜構成
Cline MCP 設定に以下を追加します:
{
"mcpServers": {
"mcp-sequentialthinking-tools": {
"command": "npx",
"args": ["-y", "mcp-sequentialthinking-tools"]
}
}
}WSL 構成の Claude デスクトップ
WSL 環境の場合は、Claude Desktop 構成に以下を追加します。
{
"mcpServers": {
"mcp-sequentialthinking-tools": {
"command": "wsl.exe",
"args": [
"bash",
"-c",
"source ~/.nvm/nvm.sh && /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-sequentialthinking-tools"
]
}
}
}API
サーバーは、構成可能なパラメータを持つ単一の MCP ツールを実装します。
シーケンシャルシンキングツール
インテリジェントなツール推奨機能を備えた、思考を通じて動的かつ反省的に問題を解決するためのツールです。
パラメータ:
thought(文字列、必須): 現在の思考ステップnext_thought_needed(ブール値、必須): 別の思考ステップが必要かどうかthought_number(整数、必須): 現在の思考番号total_thoughts(整数、必須): 必要な推定総思考数is_revision(ブール値、オプション):これが以前の考えを修正するかどうかrevises_thought(整数、オプション): 再考されている考えbranch_from_thought(整数、オプション): 分岐点の思考番号branch_id(文字列、オプション): ブランチ識別子needs_more_thoughts(ブール値、オプション): さらに考えが必要な場合current_step(オブジェクト、オプション): 現在のステップの推奨値:step_description: 何をする必要があるかrecommended_tools: 信頼スコア付きのツール推奨事項の配列expected_outcome: このステップで何が期待されるかnext_step_conditions: 次のステップの条件
previous_steps(配列、オプション):すでに推奨されている手順remaining_steps(配列、オプション): 今後のステップの概要説明
発達
設定
リポジトリをクローンする
依存関係をインストールします:
pnpm installプロジェクトをビルドします。
pnpm build開発モードで実行:
pnpm dev出版
このプロジェクトではバージョン管理に変更セットを使用しています。公開するには:
変更セットを作成します。
pnpm changesetパッケージのバージョン:
pnpm changeset versionnpm に公開:
pnpm release貢献
貢献を歓迎します!お気軽にプルリクエストを送信してください。
ライセンス
MIT ライセンス - 詳細についてはLICENSEファイルを参照してください。
謝辞
モデルコンテキストプロトコルに基づいて構築
Available Tools
1 toolsequentialthinking_toolsA
A detailed tool for dynamic and reflective problem-solving through thoughts. This tool helps analyze problems through a flexible thinking process that can adapt and evolve. Each thought can build on, question, or revise previous insights as understanding deepens.
IMPORTANT: When initializing this tool, you must pass all available tools that you want the sequential thinking process to be able to use. The tool will analyze these tools and provide recommendations for their use.
When to use this tool:
Breaking down complex problems into steps
Planning and design with room for revision
Analysis that might need course correction
Problems where the full scope might not be clear initially
Problems that require a multi-step solution
Tasks that need to maintain context over multiple steps
Situations where irrelevant information needs to be filtered out
When you need guidance on which tools to use and in what order
Key features:
You can adjust total_thoughts up or down as you progress
You can question or revise previous thoughts
You can add more thoughts even after reaching what seemed like the end
You can express uncertainty and explore alternative approaches
Not every thought needs to build linearly - you can branch or backtrack
Generates a solution hypothesis
Verifies the hypothesis based on the Chain of Thought steps
Recommends appropriate tools for each step
Provides rationale for tool recommendations
Suggests tool execution order and parameters
Tracks previous recommendations and remaining steps
Parameters explained:
thought: Your current thinking step, which can include:
Regular analytical steps
Revisions of previous thoughts
Questions about previous decisions
Realizations about needing more analysis
Changes in approach
Hypothesis generation
Hypothesis verification
Tool recommendations and rationale
next_thought_needed: True if you need more thinking, even if at what seemed like the end
thought_number: Current number in sequence (can go beyond initial total if needed)
total_thoughts: Current estimate of thoughts needed (can be adjusted up/down)
is_revision: A boolean indicating if this thought revises previous thinking
revises_thought: If is_revision is true, which thought number is being reconsidered
branch_from_thought: If branching, which thought number is the branching point
branch_id: Identifier for the current branch (if any)
needs_more_thoughts: If reaching end but realizing more thoughts needed
current_step: Current step recommendation, including:
step_description: What needs to be done
recommended_tools: Tools recommended for this step
expected_outcome: What to expect from this step
next_step_conditions: Conditions to consider for the next step
previous_steps: Steps already recommended
remaining_steps: High-level descriptions of upcoming steps
You should:
Start with an initial estimate of needed thoughts, but be ready to adjust
Feel free to question or revise previous thoughts
Don't hesitate to add more thoughts if needed, even at the "end"
Express uncertainty when present
Mark thoughts that revise previous thinking or branch into new paths
Ignore information that is irrelevant to the current step
Generate a solution hypothesis when appropriate
Verify the hypothesis based on the Chain of Thought steps
Consider available tools that could help with the current step
Provide clear rationale for tool recommendations
Suggest specific tool parameters when appropriate
Consider alternative tools for each step
Track progress through the recommended steps
Provide a single, ideally correct answer as the final output
Only set next_thought_needed to false when truly done and a satisfactory answer is reached
| Name | Required | Description | Default |
|---|---|---|---|
| branch_from_thought | No | Branching point thought number | |
| branch_id | No | Branch identifier | |
| current_step | No | Current step recommendation | |
| is_revision | No | Whether this revises previous thinking | |
| needs_more_thoughts | No | If more thoughts are needed | |
| next_thought_needed | Yes | Whether another thought step is needed | |
| previous_steps | No | Steps already recommended | |
| remaining_steps | No | High-level descriptions of upcoming steps | |
| revises_thought | No | Which thought is being reconsidered | |
| thought | Yes | Your current thinking step | |
| thought_number | Yes | Current thought number | |
| total_thoughts | Yes | Estimated total thoughts needed |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits such as adaptability ('adjust total_thoughts up or down'), revision capabilities ('question or revise previous thoughts'), and process flow ('Generates a solution hypothesis,' 'Verifies the hypothesis'), though it lacks details on error handling or performance limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is excessively long and repetitive, with multiple sections (e.g., 'Key features,' 'Parameters explained,' 'You should') that overlap in content. It includes unnecessary verbosity, such as listing 15 'You should' items, which reduces clarity and efficiency without adding proportional value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's high complexity (12 parameters, nested objects) and no annotations or output schema, the description does a good job covering the tool's purpose, usage, and behavioral aspects. However, it lacks details on output format or error conditions, which are important for such a sophisticated tool, preventing a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds some value by explaining the 'thought' parameter with examples (e.g., 'Regular analytical steps,' 'Hypothesis generation') and listing other parameters, but this largely repeats schema information, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'dynamic and reflective problem-solving through thoughts' and 'analyze problems through a flexible thinking process,' which is specific and actionable. However, with no sibling tools provided, it cannot differentiate from alternatives, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes an explicit 'When to use this tool' section with 8 specific scenarios (e.g., 'Breaking down complex problems into steps,' 'Planning and design with room for revision'), providing clear guidance on when to apply this tool. No alternatives are mentioned due to no siblings, but the context is comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
sequentialthinking_tools
TDQS
Scored across 1 tool
There is only one tool, so there is no ambiguity or overlap with other tools. The tool has a clearly defined and distinct purpose focused on sequential thinking and problem-solving.
With only one tool, naming consistency is inherently perfect. The tool name 'sequentialthinking_tools' uses snake_case, which is consistent within itself, and there are no other tools to cause inconsistency.
The server is named 'MCP Sequential Thinking Tools' and has only one tool, which suggests a thin or incomplete surface. For a domain focused on dynamic problem-solving and tool orchestration, a single tool may not adequately cover the expected scope, such as separate tools for planning, analysis, or verification steps.
The tool aims to handle complex problem-solving, planning, and tool recommendations, but as a single tool, it likely consolidates multiple functionalities into one interface. This can lead to gaps in modularity and clarity, as agents might expect separate tools for distinct phases like hypothesis generation, verification, or step tracking, rather than a monolithic solution.
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