표준 sequential-thinking MCP는 사고 연쇄 추론을 위한 훌륭한 도구를 제공하지만, 다중 에이전트 환경에서 에이전트가 근거 없는 생각을 자신 있게 환각하여 컨텍스트 창을 오염시키는 "전화 게임" 문제로 고통받습니다.
krusch-sequential-mcp는 **의미론적 타당성 게이팅(Semantic Plausibility Gating)**과 매우 안정적인 DBOS PostgreSQL 지속성 계층을 도입하여 이 문제를 해결합니다.
🧠 의미론적 타당성 게이팅: 엣지 모델 평가자를 통해 표류하거나 환각된 생각을 자율적으로 거부합니다.
💾 DBOS PostgreSQL 지속성: 모든 생각, 분기 및 수정을 dbos_thoughts 테이블에 동기식으로 지속하여 감사 가능한 추론 DAG를 생성합니다.
🛑 결정론적 상태 신뢰성: 오염된 사고 실행을 중단시켜 에이전트가 추론 경로를 재평가하도록 강제합니다.
🔌 드롭인 교체: 표준 sequential-thinking 인터페이스와 완전히 호환되면서 새로운 groundingContext 매개변수를 지원합니다.
📦 외부 의존성 제로: 타당성 평가자는 완전히 독립적이며 외부 툴킷이 필요하지 않습니다.
Related MCP server: Tyra Advanced Memory MCP Server
에이전트가 생각을 제안하면 내부 평가자가 제공된 groundingContext를 기준으로 이를 검사합니다.
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-mcp또는 MCP 설정 파일(예: claude_desktop_config.json 또는 .cursor/mcp.json)에서 구성하세요:
{
"mcpServers": {
"krusch-sequential-mcp": {
"command": "npx",
"args": ["-y", "krusch-sequential-mcp"]
}
}
}에이전트는 표준 매개변수(thought, thoughtNumber, totalThoughts, nextThoughtNeeded 등)를 사용하여 sequentialthinking 도구를 호출할 수 있습니다.
타당성 게이트를 사용하려면 도구 호출에 groundingContext 매개변수를 포함하세요:
{
"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."
}생각이 groundingContext와 충돌하기 때문에 평가자가 이를 자율적으로 거부하고 에이전트에게 접근 방식을 재고하라는 오류를 반환합니다.
변수 | 필수 | 기본값 | 설명 |
| 아니요 | (없음 — 지속성 비활성화됨) | PostgreSQL 연결 문자열 (예: |
| 아니요 |
| 타당성 검사를 위한 Ollama 서비스의 기본 URL입니다. |
| 아니요 |
| 타당성 검사에 사용되는 Ollama 모델입니다. 작고 빠른 모델이어야 합니다. |
빠른 시작을 위해 .env.example을 복사하세요:
cp .env.example .env기여를 환영합니다! 테스트가 통과하는지 확인하고 프로젝트 서식 표준을 준수해 주세요.
npm run build 및 npm start(또는 node build/index.js)를 통해 테스트를 실행하세요.
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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