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MCP verified MIT Self-run

Mcp Gemini Prompt Enhancer

mcp-andrea9293-mcp-gemini-prompt-enhancer · by andrea9293

A Model Context Protocol (MCP) server that provides a prompt optimization service for Large Language Models (LLMs) using Google Gemini, with advanced prompt engineering thanks to 22365_3_Prompt_Engineering_v7.pdf authored by Lee Boonstra

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Install

$ agentstack add mcp-andrea9293-mcp-gemini-prompt-enhancer

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
9mo ago

Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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MCP Gemini Prompt Enhancer

A Model Context Protocol (MCP) server that provides a prompt optimization service for Large Language Models (LLMs) using Google Gemini, with advanced prompt engineering support and automatic PDF asset management.

Reference PDF

The service uses as its main asset the PDF “223653PromptEngineeringv7”, a comprehensive guide on prompt engineering for Large Language Models (LLMs), authored by Lee Boonstra. The document (68 pages) covers techniques and best practices for crafting effective prompts, including zero-shot, one-shot, few-shot prompting, and configuration strategies to optimize interactions with models. It is designed to help developers and data scientists achieve better results with LLMs.

Direct download link: 223653PromptEngineeringv7.pdf

Configure MCP Client

Add to your MCP client configuration (e.g., Claude Desktop):

{
  "servers": {
    "mcp-gemini-prompt-enhancer": {
      "command": "npx",
      "args": [
        "-y",
        "@andrea9293/mcp-gemini-prompt-enhancer"
      ],
      "env": {
        "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY"
      },
      "type": "stdio"
    }
  }
}

Main Features

  • API to enhance textual prompts using prompt engineering techniques
  • Automatic download and management of reference PDF asset
  • Cross-platform compatibility (Windows, macOS, Linux)
  • FastMCP server with stdio and SSE transports (sse only for development)

Project Structure

├── src/
│   ├── core/
│   │   ├── services/
│   │   │   ├── prompt-enhancer-service.ts
│   │   │   ├── utils-service.ts
│   │   └── tools.ts
│   ├── server/
│   │   ├── http-server.ts
│   │   └── server.ts
│   └── index.ts
├── package.json
├── tsconfig.json

How it works

  • On startup, the server checks for the reference PDF in the .mcp-enhancer-service folder in the user's home directory. If not present, it downloads it automatically.
  • Exposes the enhance_prompt tool via MCP, which optimizes a textual prompt using advanced techniques and the PDF content.

Quick Start

  1. Install dependencies:

``powershell npm install ``

  1. Set the GEMINI_API_KEY environment variable with your Google Gemini key.
  2. Start the server as remote:

``powershell npm run start:http ` or with stdio transport: `powershell npm run start ``

Available API/tools

  • enhance_prompt: optimizes a textual prompt

Configuration

  • The GEMINI_API_KEY environment variable must be set to enable integration with Google Gemini.
  • The reference PDF is managed automatically.

Main Dependencies

License

MIT - see [LICENSE](LICENSE) file

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.