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Gemini MCP Server

Name: Gemini MCP Server
Author: IA-Entertainment-git-organization

by IA-Entertainment-git-organization

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Gemini-MCP-Server

Eine TypeScript-Implementierung eines Model Context Protocol (MCP)-Servers, der sich mithilfe direkter API-Aufrufe in das Gemini-Modell von Google integrieren lässt.

Merkmale

Verwendet direkte Aufrufe der Gemini-API (kein veraltetes SDK)
Unterstützt das neueste Gemini 2.0 Flash-Modell
Implementiert das MCP-Protokoll für die nahtlose Integration mit Claude
Behält den Gesprächskontext für natürliche Interaktionen bei

Related MCP server: Gemini MCP Server

MCP-Tools

Text generieren

Vom Server: Gemini

Generieren Sie Text mithilfe des Gemini-Modells mit konfigurierbaren Parametern.

Voraussetzungen

Node.js 18 oder höher
Google Gemini API-Schlüssel
Typoskript
Claude Desktop-App

Installation

Klonen Sie das Repository:

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

Installieren Sie Abhängigkeiten:

npm install

Bauen:

npm run build

Claude Desktop Integration

So verwenden Sie diesen Server mit Claude Desktop:

Öffnen Sie Claude Desktop
Gehen Sie zu Einstellungen > Entwickler
Klicken Sie auf „Konfiguration bearbeiten“.
Fügen Sie die folgende Konfiguration hinzu:

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

Ersetzen:

/path/to/gemini-mcp-server mit dem absoluten Pfad zu Ihrem Repository
your_api_key_here mit Ihrem aktuellen Google Gemini API-Schlüssel

Der Server ist jetzt in der MCP-Serverliste von Claude Desktop verfügbar.

API-Implementierung

Dieser Server verwendet direkte HTTP-Anfragen an den Gemini-API-Endpunkt. Das API-Anfrageformat folgt der offiziellen Dokumentation von 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"}]
    }]
   }'

Testen

Sie können die direkte API-Implementierung mit dem Beispielskript testen:

node dist/example_direct_api.js "Your prompt here"

Lizenz

MIT

Available Tools

1 tool

generate_textD

Name	Required	Description	Default
`maxOutputTokens`	No
`prompt`	Yes
`stream`	No
`temperature`	No
`topK`	No
`topP`	No

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 tool updatev1.0.0May 15, 2025
- First observedgenerate_text

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

D1.7/5.0

Scored 2026-04-18 10:05 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

Resources

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Appeared in Searches

A real-time voice and text AI assistant with Google Search integration and system control

Gemini-MCP-Server

Merkmale

MCP-Tools

Text generieren

Voraussetzungen

Installation

Claude Desktop Integration

API-Implementierung

Testen

Lizenz

Available Tools

TDQS

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers