MewCP Google Gemini MCP Server

होस्टेड, स्टेटलेस और मल्टीटेनेंट Gemini MCP सर्वर AI सहायकों को Google Gemini के माध्यम से मल्टीमॉडल AI क्षमताओं, सामग्री निर्माण और तर्क वर्कफ़्लो तक पहुँचने में सक्षम बनाता है।

GitHub
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दस्तावेज़

Access Google's most capable AI models through a single MCP tool.

A Model Context Protocol (MCP) server that exposes Google Gemini's API for generating text using state-of-the-art large language models.

Overview

The mewcp-gemini MCP Server provides direct access to Google's Gemini LLMs:

  • Generate high-quality text responses from natural language prompts
  • Choose between fast and capable Gemini model variants
  • Integrate Gemini's reasoning into any MCP-compatible AI workflow

Perfect for:

  • AI agents that need to delegate subtasks to a powerful LLM
  • Generating summaries, translations, code, or creative content
  • Augmenting workflows with Gemini's reasoning and language capabilities

Tools

generate_text — Generate text using Gemini LLM

Generate text using Gemini LLM

Inputs:

- `query` (string, required) — Required. Natural language prompt to send to Gemini. Any text is accepted; no length limit is enforced by this tool.
- `model` (string, optional, default: gemini-2.5-flash) — Optional. Gemini model name, e.g., 'gemini-2.5-flash' or 'gemini-2.5-pro'. Defaults to 'gemini-2.5-flash'.

Output data schema:

{
  prompt: string;
  response: string;
}

API Parameters Reference

Response Envelope

Every tool returns the same top-level envelope. Only data varies per tool.

// Success
{
  "success": true,
  "statusCode": 200,
  "retriable": false,
  "retry_after_seconds": null,
  "error": null,
  "data": { ... }
}

// Error
{
  "success": false,
  "statusCode": 400,
  "retriable": false,
  "retry_after_seconds": null,
  "error": { "code": "{ERROR_CODE}", "message": "{description}", "details": {} },
  "data": null
}
  • retriable — true when it is safe to retry (rate limit, network error, 503). false for validation and auth errors.
  • retry_after_seconds — seconds to wait before retrying; present only when retriable is true and the upstream specifies a delay.
  • error.code — machine-readable string: VALIDATION_ERROR, AUTH_ERROR, UPSTREAM_ERROR, SERVER_ERROR.

Getting Your Gemini API Key

Steps
  1. Go to Google AI Studio API Keys
  2. Sign in with your Google account and navigate to the API keys section
  3. Click Create API Key
  4. Copy the generated key — you will only see it once

Troubleshooting

Missing or Invalid Headers
  • Cause: API key not provided in request headers or incorrect format
  • Solution:
    1. Verify Authorization: Bearer YOUR_API_KEY and X-Mewcp-Credential-Id: CREDENTIAL-ID headers are present
    2. Check API key is active in your MewCP account
Insufficient Credits
  • Cause: API calls have exceeded your request limits
  • Solution:
    1. Check credit usage in your Curious Layer dashboard
    2. Upgrade to a paid plan or add credits for higher limits
    3. Contact support for credit adjustments
Credential Not Connected
  • Cause: No Gemini credential linked to your account
  • Solution:
    1. Go to Credentials in your MewCP dashboard
    2. Add your API key (static)
    3. Retry the request with the correct X-Mewcp-Credential-Id header
Malformed Request Payload
  • Cause: JSON payload is invalid or missing required fields
  • Solution:
    1. Validate JSON syntax before sending
    2. Ensure all required tool parameters are included
    3. Check parameter types match expected values
Server Not Found
  • Cause: Incorrect server name in the API endpoint
  • Solution:
    1. Verify endpoint format: mewcp-gemini/mcp/generate_text
    2. Use correct server name from documentation
    3. Check available servers in your Curious Layer account
Gemini API Error
  • Cause: Upstream Gemini API returned an error
  • Solution:
    1. Check Gemini service status at Google Status Page
    2. Verify your credential has the required permissions
    3. Review the error message for specific details
Resources