Стандартный MCP-инструмент sequential-thinking отлично подходит для пошагового рассуждения, но страдает от проблемы «испорченного телефона» в многоагентных средах, где агенты могут уверенно галлюцинировать необоснованные мысли, отравляющие контекстное окно.
krusch-sequential-mcp решает эту проблему, внедряя семантический контроль правдоподобия (Semantic Plausibility Gating) наряду с высоконадежным уровнем сохранения данных в DBOS PostgreSQL.
🧠 Семантический контроль правдоподобия: Автономно отклоняет отклонившиеся или галлюцинированные мысли с помощью пограничной модели-оценщика.
💾 Сохранение в DBOS PostgreSQL: Синхронно сохраняет каждую мысль, ветку и редакцию в таблицу dbos_thoughts, создавая проверяемый направленный ациклический граф (DAG) рассуждений.
🛑 Детерминированная надежность состояния: Останавливает выполнение «отравленных» мыслей, заставляя агентов переоценивать свой путь рассуждений.
🔌 Прямая замена: Полностью совместим со стандартным интерфейсом sequential-thinking и поддерживает новый параметр groundingContext.
📦 Отсутствие внешних зависимостей: Оценщик правдоподобия полностью автономен — не требуется никаких внешних инструментов.
Related MCP server: Tyra Advanced Memory MCP Server
Когда агент предлагает мысль, внутренний оценщик проверяет её на соответствие предоставленному groundingContext.
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-mcpИли настройте его в файле конфигурации MCP (например, claude_desktop_config.json или .cursor/mcp.json):
{
"mcpServers": {
"krusch-sequential-mcp": {
"command": "npx",
"args": ["-y", "krusch-sequential-mcp"]
}
}
}Агенты могут вызывать инструмент sequentialthinking со стандартными параметрами (thought, thoughtNumber, totalThoughts, nextThoughtNeeded и т. д.).
Чтобы задействовать шлюз правдоподобия, включите параметр groundingContext в вызов инструмента:
{
"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."
}Поскольку мысль противоречит groundingContext, оценщик автономно отклонит её, вернув агенту ошибку с требованием переосмыслить подход.
Переменная | Обязательно | По умолчанию | Описание |
| Нет | (нет — сохранение отключено) | Строка подключения к PostgreSQL (например, |
| Нет |
| Базовый URL сервиса Ollama для проверок на правдоподобие. |
| Нет |
| Модель Ollama, используемая для проверки правдоподобия. Рекомендуется использовать небольшую и быструю модель. |
Скопируйте .env.example для быстрого старта:
cp .env.example .envМы приветствуем вклад в проект! Пожалуйста, убедитесь, что ваши тесты проходят успешно и соответствуют стандартам форматирования проекта.
Запускайте тесты через npm run build и npm start (или node build/index.js).
Лицензия MIT © 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. Dates show when Glama detected each change.
v1.0.0sequentialthinkingOnly 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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