Gemini Thinking Server
Protocolo de contexto del modelo - Gemini Thinking Server
Esta es una implementación del Protocolo de Contexto de Modelo (MCP) que se integra con la API Gemini de Google para proporcionar capacidades de pensamiento analítico sin generación de código.
Descripción general
Gemini Thinking Server es un servidor MCP especializado que aprovecha el modelo Gemini de Google para ofrecer pensamiento secuencial y capacidades de resolución de problemas. Permite:
Descomponer problemas complejos en pasos
Planificación y diseño con espacio para revisión
Análisis que podría requerir corrección de rumbo
Problemas cuyo alcance total podría no estar claro inicialmente
Related MCP server: gpal
Características
Pensamiento impulsado por Géminis : utiliza las capacidades analíticas de Géminis para generar respuestas reflexivas.
Metacomentario : proporciona información sobre el proceso de razonamiento.
Niveles de confianza : Indica qué tan seguro está Géminis en su análisis.
Caminos alternativos : sugiere diferentes enfoques al problema
Pensamientos ramificados : permite la exploración de diferentes caminos de pensamiento.
Capacidad de revisión : Apoya la revisión de pensamientos previos.
Persistencia de sesión : guardar y reanudar sesiones de análisis
Instalación
# Clone the repository
git clone <repository-url>
# Install dependencies
npm install
# Build the project
npm run buildUso
Configuración del entorno
Antes de ejecutar el servidor, debe configurar su clave API de Gemini:
export GEMINI_API_KEY=your_api_key_hereEjecución del servidor
node dist/gemini-index.jsParámetros de la herramienta
La herramienta geminithinking acepta los siguientes parámetros:
query(obligatoria): La pregunta o problema a analizarcontext(opcional): información de contexto adicionalapproach(opcional): Enfoque sugerido para el problemapreviousThoughts(opcional): Matriz de pensamientos previos para contextothought(opcional): Tu paso de pensamiento actual (si está vacío, será generado por Géminis)nextThoughtNeeded(obligatorio): si se necesita otro paso de pensamientothoughtNumber(obligatorio): Número de pensamiento actualtotalThoughts(obligatorio): Estimación del total de pensamientos necesariosisRevision(opcional): si esto revisa el pensamiento previorevisesThought(opcional): ¿Qué pensamiento se está reconsiderando?branchFromThought(opcional): Número de pensamiento del punto de ramificaciónbranchId(opcional): identificador de ramaneedsMoreThoughts(opcional): Si se necesitan más pensamientos
Gestión de sesiones
La herramienta también admite comandos de gestión de sesiones:
sessionCommand: Comando para administrar sesiones ('guardar', 'cargar', 'obtener estado')sessionPath: Ruta para guardar o cargar el archivo de sesión (necesario para los comandos 'guardar' y 'cargar')
Ejemplo: Guardar una sesión
{
"sessionCommand": "save",
"sessionPath": "/path/to/save/session.json",
"query": "dummy",
"thoughtNumber": 1,
"totalThoughts": 1,
"nextThoughtNeeded": false
}Ejemplo: Cargar una sesión
{
"sessionCommand": "load",
"sessionPath": "/path/to/load/session.json",
"query": "dummy",
"thoughtNumber": 1,
"totalThoughts": 1,
"nextThoughtNeeded": false
}Ejemplo: Obtener el estado de la sesión
{
"sessionCommand": "getState",
"query": "dummy",
"thoughtNumber": 1,
"totalThoughts": 1,
"nextThoughtNeeded": false
}Ejemplo
A continuación se muestra un ejemplo de cómo utilizar la herramienta:
{
"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
}Formato de respuesta
El servidor responde con:
{
"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"]
}Clientes de ejemplo
Se proporcionan varios clientes de ejemplo para demostrar diferentes casos de uso:
sample-client.js: Ejemplo básico de clienteexample-usage.js: Ejemplo de uso específicocodebase-analysis-example.js: Ejemplo de análisis de código basesession-example.js: Ejemplo que demuestra la persistencia de la sesiónadvanced-filtering-example.js: Ejemplo que demuestra el filtrado semántico avanzado
Para ejecutar el ejemplo de sesión:
node dist/session-example.jsPara ejecutar el ejemplo de filtrado avanzado:
node dist/advanced-filtering-example.jsLicencia
Instituto Tecnológico de Massachusetts (MIT)
Available Tools
1 toolgeminithinkingA
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 |
TDQS
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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.1- First observed
geminithinking
TDQS
Scored 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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