Skip to main content
Glama

servidor gemini-mcp

Una implementación de TypeScript de un servidor de Protocolo de contexto de modelo (MCP) que se integra con el modelo Gemini de Google mediante llamadas API directas.

Características

  • Utiliza llamadas directas a la API de Gemini (sin SDK obsoleto)

  • Admite el último modelo Flash Gemini 2.0

  • Implementa el protocolo MCP para una integración perfecta con Claude

  • Mantiene el contexto de la conversación para interacciones naturales.

Related MCP server: Gemini MCP Server

Herramientas MCP

generar_texto

Desde el servidor: gemini

Genere texto utilizando el modelo Gemini con parámetros configurables.

Prerrequisitos

  • Node.js 18 o superior

  • Clave API de Google Gemini

  • Mecanografiado

  • Aplicación de escritorio Claude

Instalación

  1. Clonar el repositorio:

git clone https://github.com/YOUR-USERNAME/gemini-mcp-server.git
cd gemini-mcp-server
  1. Instalar dependencias:

npm install
  1. Construir:

npm run build

Integración de escritorio de Claude

Para utilizar este servidor con Claude Desktop:

  1. Abra Claude Desktop

  2. Vaya a Configuración > Desarrollador

  3. Haga clic en "Editar configuración"

  4. Agregue la siguiente configuración:

"gemini": {
  "command": "node",
  "args": ["path\\to\\dist\\gemini_mcp_server.js"],
  "env": {
    "GEMINI_API_KEY": "gemini_api_key"
  },
  "cwd": "path\\to\\gemini-mcp-server"
}

Reemplazar:

  • /path/to/gemini-mcp-server con la ruta absoluta a su repositorio

  • your_api_key_here con su clave API de Google Gemini real

El servidor ahora estará disponible en la lista de servidores MCP de Claude Desktop.

Implementación de API

Este servidor utiliza solicitudes HTTP directas al punto final de la API de Gemini. El formato de solicitud a la API se ajusta a la documentación oficial de Google:

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
  "contents": [{
    "parts":[{"text": "Explain how AI works"}]
    }]
   }'

Pruebas

Puede probar la implementación directa de la API utilizando el script de ejemplo:

node dist/example_direct_api.js "Your prompt here"

Licencia

Instituto Tecnológico de Massachusetts (MIT)

Available Tools

1 tool
generate_textD
NameRequiredDescriptionDefault
maxOutputTokensNo
promptYes
streamNo
temperatureNo
topKNo
topPNo

TDQS

D1/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

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. 1 tool updatev1.0.0
    • First observedgenerate_text

TDQS

D1.7/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'generate_text' has a distinct purpose by default.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'generate_text' follows a clear verb_noun pattern.

Tool Count2/5

One tool is too few for a server named 'Gemini MCP Server', which suggests a broader scope like interacting with Gemini AI services. A single text generation tool feels thin and incomplete for such a domain.

Completeness1/5

The server is severely incomplete for its implied purpose. With only a text generation tool, it lacks essential operations like chat interactions, model selection, or other AI functionalities expected from a Gemini server, leading to significant gaps.

Maintenance

ActivityInactive
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    A TypeScript server that integrates Google's Gemini Pro model with Claude Desktop through the Model Context Protocol, allowing Claude users to access Gemini's text generation capabilities.
    7
    130 npm
    12
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    A server implementing the Model Context Protocol that enables AI assistants like Claude to interact with Google's Gemini API for text generation, text analysis, and chat conversations.
    -
  • A
    license
    B
    quality
    D
    maintenance
    A Model Context Protocol server that enables Claude Desktop to interact with Google's Gemini 2.5 Pro Experimental AI model, with features like Google Search integration and token usage reporting.
    2
    16 npm
    4
    Apache 2.0