mcp-sequentialthinking-tools
mcp-sequentialthinking-tools
순차적 추론 단계를 기록하기 위한 경량 MCP 서버입니다. 이 서버는 기록, 분기, 수정 메타데이터를 포함하는 스크래치패드이며, 모델이 작성한 도구 계획에 대한 선택적 검증 기능을 제공합니다.
이 서버는 사용자의 다른 MCP 도구를 검색하거나 모델을 대신하여 도구를 선택하지 않습니다. available_tools와 recommended_tools를 전달하면, 서버는 추천된 이름이 실제로 존재하는지 검증하고 해당 단계를 저장합니다.
사용 이유
명시적이고 검토 가능한 추론이 필요한 작업에 사용하세요:
복잡한 문제를 단계별로 세분화할 때;
계획을 수정하거나 분기할 때;
세션별로 짧은 추론 기록을 유지할 때;
제공된 도구 목록을 기준으로 도구 계획 이름을 검증할 때;
긴 에이전트 실행 중에 추론 기록을 지우거나 검사할 때.
단순한 요청에는 사용하지 마세요. 오버헤드가 추가됩니다.
Related MCP server: Sequential-Thinking
도구
sequentialthinking_tools
하나의 사고 과정을 기록합니다.
필수 매개변수:
thought— 현재 추론 단계thought_number— 현재 단계 번호total_thoughts— 현재 예상치;thought_number보다 낮으면 자동으로 상향 조정됨next_thought_needed— 추가 사고가 필요한지 여부
선택적 매개변수:
session_id— 기록 버킷; 기본값은defaultis_revision,revises_thoughtbranch_from_thought,branch_idneeds_more_thoughtsavailable_tools— 도구 이름 배열 또는{ name, description }객체recommended_tools— 검증/저장할 모델 작성 추천 도구remaining_steps— 향후 단계에 대한 짧은 목록
예시:
{
"session_id": "svelte-debug",
"thought": "First inspect the route files, then run the failing check.",
"thought_number": 1,
"total_thoughts": 3,
"next_thought_needed": true,
"available_tools": ["read", "bash"],
"recommended_tools": [
{
"tool_name": "read",
"confidence": 0.9,
"rationale": "Need to inspect the relevant files before editing.",
"priority": 1
}
]
}recommended_tools에 available_tools에 없는 이름이 포함되어 있으면, 호출은 isError: true를 반환하고 해당 사고를 저장하지 않습니다.
보안 상태
이 서버는 사고 텍스트, 도구 설명, 근거 및 남은 단계 텍스트를 신뢰할 수 없는 입력으로 취급합니다. 프롬프트 주입과 유사한 텍스트는 저장되거나 기록에서 반환되기 전에 스캔 및 삭제됩니다. 삭제가 포함된 호출에는 일치하는 필드를 보여주는 security_warnings가 포함됩니다.
이는 방어적 필터링이며, 임의의 적대적 텍스트가 안전하다는 보장은 아닙니다. 사고나 도구 설명에 비밀 정보를 넣지 마십시오.
get_thinking_history
세션에 저장된 사고 기록을 반환합니다.
매개변수:
session_id— 기본값은defaultbranch_id— 선택적 분기 필터limit— 반환할 최대 기록 수; 기본값50, 최대500
clear_thinking_history
하나의 세션 또는 모든 세션을 지웁니다.
매개변수:
session_id— 기본값은defaultall_sessions— 모든 기록 버킷 지우기
프롬프트
sequential-thinking-guidance
모델에게 이 서버를 외부 추론 엔진이 아닌 스크래치패드 및 검증기로서 정직하게 사용하는 방법을 알려주는 짧은 프롬프트입니다.
구성
Claude Desktop / 호환되는 MCP 클라이언트
{
"mcpServers": {
"mcp-sequentialthinking-tools": {
"command": "npx",
"args": ["-y", "mcp-sequentialthinking-tools"],
"env": {
"MAX_HISTORY_SIZE": "1000"
}
}
}
}MAX_HISTORY_SIZE는 세션당 적용되며 기본값은 1000입니다.
이 서버는 tmcp를 사용하며, 표준 Content-Length 프레임 MCP 메시지와 이전 tmcp 도구에서 사용하는 줄바꿈으로 구분된 JSON을 모두 허용하는 작은 stdio 전송을 포함합니다.
개발
pnpm install
pnpm test
pnpm build
pnpm check이 프로젝트는 빌드, 테스트, 포맷 및 린트 오케스트레이션을 위해 vite-plus를 사용합니다.
게시
pnpm changeset
pnpm changeset version
pnpm release라이선스
MIT 라이선스 — LICENSE를 참조하십시오.
감사의 말
Model Context Protocol을 기반으로 구축됨
Available Tools
1 toolsequentialthinking_toolsA 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: This server facilitates sequential thinking with MCP tool coordination. The LLM analyzes available tools and their descriptions to make intelligent recommendations, which are then tracked and organized by this server. 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: - available_mcp_tools: Array of MCP tool names that are available for use (e.g., ["mcp-omnisearch", "mcp-turso-cloud"]) - 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: 1. Start with an initial estimate of needed thoughts, but be ready to adjust 2. Feel free to question or revise previous thoughts 3. Don't hesitate to add more thoughts if needed, even at the "end" 4. Express uncertainty when present 5. Mark thoughts that revise previous thinking or branch into new paths 6. Ignore information that is irrelevant to the current step 7. Generate a solution hypothesis when appropriate 8. Verify the hypothesis based on the Chain of Thought steps 9. Consider available tools that could help with the current step 10. Provide clear rationale for tool recommendations 11. Suggest specific tool parameters when appropriate 12. Consider alternative tools for each step 13. Track progress through the recommended steps 14. Provide a single, ideally correct answer as the final output 15. Only set next_thought_needed to false when truly done and a satisfactory answer is reachedA
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: This server facilitates sequential thinking with MCP tool coordination. The LLM analyzes available tools and their descriptions to make intelligent recommendations, which are then tracked and organized by this server.
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:
available_mcp_tools: Array of MCP tool names that are available for use (e.g., ["mcp-omnisearch", "mcp-turso-cloud"])
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 |
|---|---|---|---|
| available_mcp_tools | Yes | Array of MCP tool names available for use (e.g., ["mcp-omnisearch", "mcp-turso-cloud"]) | |
| thought | Yes | Your current thinking step | |
| next_thought_needed | Yes | Whether another thought step is needed | |
| thought_number | Yes | Current thought number | |
| total_thoughts | Yes | Estimated total thoughts needed | |
| is_revision | No | Whether this revises previous thinking | |
| revises_thought | No | Which thought is being reconsidered | |
| branch_from_thought | No | Branching point thought number | |
| branch_id | No | Branch identifier | |
| needs_more_thoughts | No | If more thoughts are needed | |
| current_step | No | Current step recommendation | |
| previous_steps | No | Steps already recommended | |
| remaining_steps | No | High-level descriptions of upcoming steps |
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 the tool's dynamic nature (e.g., adjusting thoughts, revising, branching), its role in MCP tool coordination, and expected behaviors like hypothesis generation and verification. However, it lacks details on error handling, performance limits, or authentication needs, which are minor gaps.
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 overly verbose and repetitive, with sections like 'Parameters explained' and 'You should' that could be condensed. While well-structured with clear headings, it includes redundant information (e.g., repeating tool features in multiple sections), reducing efficiency. Every sentence adds value, but many could be more concise.
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 (13 parameters, nested objects, no output schema, and no annotations), the description is exceptionally complete. It covers purpose, usage, features, parameter explanations, and detailed instructions, providing all necessary context for an agent to understand and invoke the tool correctly without relying on structured fields.
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?
Despite 100% schema description coverage, the description adds significant value by explaining parameter semantics in detail. It provides context for each parameter (e.g., 'thought' can include revisions, questions, hypotheses; 'current_step' includes tool recommendations with rationale), clarifies usage patterns, and offers examples, going well beyond the schema's basic descriptions.
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?
Tautological: description restates name/title.
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 provides explicit 'When to use this tool' with 8 bullet points covering scenarios like complex problems, planning with revision, unclear scope, multi-step solutions, and tool guidance. It also includes a 'You should' section with 15 detailed instructions on how to use the tool effectively, offering comprehensive guidance on when and how to apply it.
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. Dates show when Glama detected each change.
1 tool update
v1.0.0- Changed
sequentialthinking_tools7 fields changed- added
Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#" - changed
Input schema / properties / branch_from_thought / typePrevious value: -"integer"New value: +"number" - added
Input schema / properties / current_step / properties / recommended_tools / items / properties / suggested_inputs / additionalPropertiesAdded value: +{} - added
Input schema / properties / previous_steps / items / properties / recommended_tools / items / properties / suggested_inputs / additionalPropertiesAdded value: +{} - changed
Input schema / properties / revises_thought / typePrevious value: -"integer"New value: +"number" - changed
Input schema / properties / thought_number / typePrevious value: -"integer"New value: +"number" - changed
Input schema / properties / total_thoughts / typePrevious value: -"integer"New value: +"number"
1 tool update
- First observed
sequentialthinking_tools
TDQS
With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool 'sequentialthinking_tools' has a singular, clearly defined purpose for dynamic problem-solving, so an agent cannot misselect between non-existent alternatives.
Since there is only one tool, naming consistency is inherently perfect. The tool name uses a consistent snake_case format, and there are no other tools to compare it against, so no inconsistencies can arise.
A single tool is too few for the server's stated purpose of facilitating sequential thinking with MCP tool coordination. The tool description implies a need for interaction with multiple tools, but the server only provides one meta-tool, which feels thin and limits functionality for the intended scope.
The server is severely incomplete for its domain. It lacks direct tools for the actual operations it coordinates (e.g., search, data retrieval, execution), relying solely on a meta-tool for recommendations. This creates a significant gap, as agents cannot perform the underlying tasks without external tools, leading to potential dead ends in workflows.
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