이는 Google의 Gemini API와 통합되어 코드 생성 없이 분석적 사고 기능을 제공하는 MCP(Model Context Protocol)의 구현입니다.
제미니 씽킹 서버는 구글의 제미니 모델을 활용하여 순차적 사고 및 문제 해결 기능을 제공하는 전문 MCP 서버입니다. 다음과 같은 기능을 제공합니다.
복잡한 문제를 단계별로 분해
수정의 여지를 둔 계획 및 설계
진로 수정이 필요할 수 있는 분석
전체 범위가 처음에는 명확하지 않을 수 있는 문제
Related MCP server: gpal
쌍둥이자리 의 분석 능력을 활용하여 사려 깊은 반응을 생성합니다.
메타 해설 : 추론 과정에 대한 통찰력을 제공합니다.
신뢰 수준 : 쌍둥이자리가 분석에 얼마나 자신감을 가지고 있는지를 나타냅니다.
대안 경로 : 문제에 대한 다양한 접근 방식을 제안합니다.
분기 생각 : 다양한 생각 경로를 탐색할 수 있습니다.
수정 기능 : 이전 생각을 수정하는 것을 지원합니다.
세션 지속성 : 분석 세션 저장 및 재개
지엑스피1
서버를 실행하기 전에 Gemini API 키를 설정해야 합니다.
export GEMINI_API_KEY=your_api_key_herenode dist/gemini-index.jsgeminithinking 도구는 다음과 같은 매개변수를 허용합니다.
query (필수): 분석할 질문이나 문제
context (선택 사항): 추가 컨텍스트 정보
approach (선택 사항): 문제에 대한 제안된 접근 방식
previousThoughts (선택 사항): 맥락을 위한 이전 생각의 배열
thought (선택 사항): 현재 생각 단계(비어 있으면 쌍둥이자리가 생성함)
nextThoughtNeeded (필수): 다른 사고 단계가 필요한지 여부
thoughtNumber (필수): 현재 생각 번호
totalThoughts (필수): 필요한 총 생각 수 추정
isRevision (선택 사항): 이것이 이전 생각을 수정하는지 여부
revisesThought (선택 사항): 어떤 생각이 재고되고 있습니까?
branchFromThought (선택 사항): 분기점 생각 번호
branchId (선택 사항): 지점 식별자
needsMoreThoughts (선택 사항): 더 많은 생각이 필요한 경우
이 도구는 또한 세션 관리 명령을 지원합니다.
sessionCommand : 세션을 관리하는 명령('save', 'load', 'getState')
sessionPath : 세션 파일을 저장하거나 로드할 경로('save' 및 'load' 명령에 필요)
{
"sessionCommand": "save",
"sessionPath": "/path/to/save/session.json",
"query": "dummy",
"thoughtNumber": 1,
"totalThoughts": 1,
"nextThoughtNeeded": false
}{
"sessionCommand": "load",
"sessionPath": "/path/to/load/session.json",
"query": "dummy",
"thoughtNumber": 1,
"totalThoughts": 1,
"nextThoughtNeeded": false
}{
"sessionCommand": "getState",
"query": "dummy",
"thoughtNumber": 1,
"totalThoughts": 1,
"nextThoughtNeeded": false
}도구를 사용하는 방법의 예는 다음과 같습니다.
{
"query": "How might we design a sustainable urban transportation system?",
"context": "The city has 500,000 residents and currently relies heavily on personal vehicles.",
"approach": "Consider environmental, economic, and social factors.",
"thoughtNumber": 1,
"totalThoughts": 5,
"nextThoughtNeeded": true
}서버는 다음과 같이 응답합니다.
{
"thought": "The generated thought from Gemini",
"thoughtNumber": 1,
"totalThoughts": 5,
"nextThoughtNeeded": true,
"branches": [],
"thoughtHistoryLength": 1,
"metaComments": "Meta-commentary about the reasoning",
"confidenceLevel": 0.85,
"alternativePaths": ["Alternative approach 1", "Alternative approach 2"]
}다양한 사용 사례를 보여주기 위해 몇 가지 예제 클라이언트가 제공됩니다.
sample-client.js : 기본 클라이언트 예제
example-usage.js : 구체적인 사용 예
codebase-analysis-example.js : 코드베이스 분석 예시
session-example.js : 세션 지속성을 보여주는 예
advanced-filtering-example.js : 고급 의미 필터링을 보여주는 예
세션 예제를 실행하려면:
node dist/session-example.js고급 필터링 예제를 실행하려면:
node dist/advanced-filtering-example.jsMIT
A detailed tool for dynamic and reflective problem-solving through Gemini AI. This tool helps analyze problems through a flexible thinking process powered by Google's Gemini model. Each thought can build on, question, or revise previous insights as understanding deepens.
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
Key features:
Leverages Gemini AI for deep analytical thinking
Provides meta-commentary on the reasoning process
Indicates confidence levels for generated thoughts
Suggests alternative approaches when relevant
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
Session persistence: save and resume your analysis sessions
Parameters explained:
query: The question or problem to be analyzed
context: Additional context information (e.g., code snippets, background)
approach: Suggested approach to the problem (optional)
previousThoughts: Array of previous thoughts for context
thought: The current thinking step (if empty, will be generated by Gemini)
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
metaComments: Meta-commentary from Gemini about its reasoning process
confidenceLevel: Gemini's confidence in the generated thought (0-1)
alternativePaths: Alternative approaches suggested by Gemini
Session commands:
sessionCommand: Command to manage sessions ('save', 'load', 'getState')
sessionPath: Path to save or load the session file (required for 'save' and 'load' commands)
You should:
Start with a clear query and any relevant context
Let Gemini generate thoughts by not providing the 'thought' parameter
Review the generated thoughts and meta-commentary
Feel free to revise or branch thoughts as needed
Consider alternative paths suggested by Gemini
Only set next_thought_needed to false when truly done
Use session commands to save your progress and resume later
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The question or problem to analyze | |
| context | No | Additional context information | |
| thought | No | Your current thinking step (if empty, will be generated by Gemini) | |
| approach | No | Suggested approach to the problem | |
| branchId | No | Branch identifier | |
| isRevision | No | Whether this revises previous thinking | |
| sessionPath | No | Path to save or load the session file | |
| metaComments | No | Meta-commentary about the reasoning process | |
| thoughtNumber | Yes | Current thought number | |
| totalThoughts | Yes | Estimated total thoughts needed | |
| revisesThought | No | Which thought is being reconsidered | |
| sessionCommand | No | Command to manage sessions ('save', 'load', 'getState') | |
| confidenceLevel | No | Confidence level in the generated thought (0-1) | |
| alternativePaths | No | Alternative approaches suggested | |
| previousThoughts | No | Array of previous thoughts for 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?
With no annotations, the description fully covers behavioral aspects like meta-commentary, confidence levels, revision, branching, and session persistence. However, it omits potential costs or rate limits associated with the Gemini AI backend, slightly reducing transparency.
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 well-organized with sections and bullet points, but it is overly verbose. Some redundancy exists between the 'when to use' list and 'key features'. Removing repetition would improve conciseness while retaining clarity.
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 complexity and lack of output schema, the description adequately explains usage flow and available actions. However, it does not explicitly specify the output structure (e.g., JSON containing generated thought, meta-comments, etc.), leaving minor ambiguity.
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 coverage is 100%, so baseline is 3. The description adds extra context beyond schema descriptions, e.g., explaining that an empty 'thought' parameter will be AI-generated and that 'thought_number' can exceed initial estimates. This adds meaningful value.
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 is for dynamic, reflective problem-solving via Gemini AI. It includes specific usage scenarios and features. However, with no sibling tools, differentiation is not assessed, but the purpose is clear and distinct from a generic 'think' tool.
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 a detailed list of when to use the tool, including breaking down complex problems, planning, and analysis needing course correction. It does not explicitly mention when not to use it, but the extensive positive guidance compensates.
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.
v1.0.1geminithinkingScored across 1 tool
Only one tool exists, so there is no risk of confusion or overlap with other tools.
With a single tool, naming consistency is inherently perfect; the name 'geminithinking' clearly describes its purpose.
The server has only one tool, which feels thin for a domain that could benefit from separate tools for sessions, branching, or analysis management. However, the single tool is feature-rich.
The tool covers all expected functionalities for a deep thinking assistant: querying, context, revisions, branching, session persistence, and meta-commentary. No obvious gaps.
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