標準の sequential-thinking MCP は思考連鎖推論のための優れたツールですが、マルチエージェント環境では「伝言ゲーム」の問題に悩まされます。エージェントが根拠のない思考を自信満々にハルシネーション（幻覚）し、コンテキストウィンドウを汚染してしまうのです。
krusch-sequential-mcp は、セマンティック妥当性ゲートと、非常に信頼性の高い DBOS PostgreSQL永続化レイヤーを導入することで、この問題を解決します。
🧠 セマンティック妥当性ゲート: エッジモデル評価器を通じて、逸脱した思考やハルシネーションを自律的に拒否します。
💾 DBOS PostgreSQL永続化: すべての思考、ブランチ、リビジョンを dbos_thoughts テーブルに同期的に保存し、監査可能な推論のDAG（有向非巡回グラフ）を作成します。
🛑 決定論的な状態の信頼性: 汚染された思考の実行を停止し、エージェントに推論パスの再評価を強制します。
🔌 ドロップイン置換: 標準の sequential-thinking インターフェースと完全な互換性を持ちつつ、新しい groundingContext パラメータをサポートします。
📦 外部依存関係ゼロ: 妥当性評価器は完全に自己完結しており、外部ツールキットは不要です。
Related MCP server: Tyra Advanced Memory MCP Server
エージェントが思考を提案すると、内部評価器が提供された groundingContext に照らしてそれをスクリーニングします。
graph TD;
A[Agent Thought Proposed] --> B{Grounding Context Provided?};
B -- No --> C[Accept & Persist to DBOS];
B -- Yes --> D[Edge Model Evaluator];
D -- Plausible --> C;
D -- Hallucinated/Drifted --> E[Reject Thought];
E --> F[Return Soft Error to Agent];
F --> G[Agent Re-evaluates];npm install -g krusch-sequential-mcpまたは、MCP設定ファイル（例: claude_desktop_config.json や .cursor/mcp.json）で設定します：
{
"mcpServers": {
"krusch-sequential-mcp": {
"command": "npx",
"args": ["-y", "krusch-sequential-mcp"]
}
}
}エージェントは、標準パラメータ（thought、thoughtNumber、totalThoughts、nextThoughtNeeded など）を使用して sequentialthinking ツールを呼び出すことができます。
妥当性ゲートを有効にするには、ツール呼び出しに groundingContext パラメータを含めてください：
{
"thought": "Since the user is asking about the database schema, I will assume it uses MongoDB and write a query for it.",
"thoughtNumber": 1,
"totalThoughts": 3,
"nextThoughtNeeded": true,
"groundingContext": "The current codebase exclusively uses DBOS PostgreSQL for persistence. No NoSQL databases are present."
}思考が groundingContext と矛盾するため、評価器は自律的にそれを拒否し、エージェントにアプローチの再考を促すエラーを返します。
変数 | 必須 | デフォルト | 説明 |
| いいえ | (なし — 永続化無効) | PostgreSQL接続文字列（例: |
| いいえ |
| 妥当性チェックを行うOllamaサービスのベースURL。 |
| いいえ |
| 妥当性スクリーニングに使用するOllamaモデル。小型で高速なモデルを推奨します。 |
クイックスタートのために .env.example をコピーしてください：
cp .env.example .envコントリビューションを歓迎します！テストがパスすること、およびプロジェクトのフォーマット基準に従っていることを確認してください。
テストは npm run build および npm start（または node build/index.js）で実行できます。
MIT License © 2026 kruschdev
A detailed tool for dynamic and reflective problem-solving through thoughts. Augmented with Semantic Plausibility Gating.
| Name | Required | Description | Default |
|---|---|---|---|
| thought | Yes | Your current thinking step | |
| branchId | No | Branch identifier | |
| isRevision | No | Whether this revises previous thinking | |
| thoughtNumber | Yes | Current thought number | |
| totalThoughts | Yes | Estimated total thoughts needed | |
| revisesThought | No | Which thought is being reconsidered | |
| groundingContext | No | OPTIONAL: Provide the source context for this thought. The server will independently verify the plausibility of your thought against this context. | |
| branchFromThought | No | Branching point thought number | |
| needsMoreThoughts | No | If more thoughts are needed | |
| nextThoughtNeeded | Yes | Whether another thought step is needed |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It mentions 'Semantic Plausibility Gating' which hints at a verification mechanism, but does not explain how it works, what data is stored, or any side effects. The schema's groundingContext field description provides some behavior, but the main description is insufficient for an agent to understand the tool's operational characteristics.
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 very short at one sentence, which is lean but not necessarily well-structured. It front-loads the core concept, but the single sentence lacks detail that could be organized in a more informative way. It is not overly verbose, but it doesn't make effective use of its brevity.
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?
For a complex tool with 10 parameters and no output schema, the description is inadequate. It doesn't explain the workflow (e.g., how to sequence thoughts, the meaning of branchId, revision, nextThoughtNeeded), nor does it describe the plausibility gating behavior beyond naming it. The schema helps but the description leaves the agent without context on how to use the tool effectively.
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?
All 10 parameters have schema descriptions, so the baseline is 3. The main description adds no parameter-specific meaning, and it doesn't mention any relationships between params. However, given 100% schema coverage, the schema itself is sufficient for understanding parameters.
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 describes the tool as 'for dynamic and reflective problem-solving through thoughts', which conveys the general domain but lacks a specific action verb (e.g., submit, record) or resource. The name 'sequentialthinking' partially compensates, but the description alone doesn't clarify what the tool does beyond generic problem-solving.
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?
No guidance on when to use this tool versus other tools. No alternatives are mentioned, and no context is provided about the appropriate use case. The description simply states what it is without indications of when it should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0sequentialthinkingScored across 1 tool
Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is singular and clear.
With a single tool, naming consistency is trivially satisfied. The name 'sequentialthinking' is descriptive and matches the server's focus.
The server has exactly one tool, which feels minimal. While it is appropriate for a focused sequential thinking utility, the count is on the borderline of being too thin.
The tool appears to provide a comprehensive capability for sequential thinking and problem-solving. However, being the only tool, there may be missing auxiliary operations like reset or history, though no obvious gaps are evident.
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