Question 1

What is GemForge-mcp?

Accepted Answer

GemForge-mcp is a Model Context Protocol (MCP) server that provides specialized tools for interacting with Google's Gemini AI models, Claude and other MCP-compatible hosts. It offers intelligent model selection, advanced file handling, and optimized prompts.

Question 2

What is MCP (Model Context Protocol)?

Accepted Answer

MCP is an open protocol that standardizes how applications provide context to LLMs (Large Language Models), facilitating seamless integration and communication between different AI models and applications.

Question 3

How do I install GemForge-mcp?

Accepted Answer

Clone the repository, install dependencies using `npm install`, and build the project with `npm run build`.

Question 4

How do I configure GemForge-mcp?

Accepted Answer

Create a `.env` file in the root directory and set the `GEMINI_API_KEY`, `DEFAULT_MODEL_ID`, and `GEMINI_PAID_TIER` variables.

Question 5

How do I run the GemForge-mcp server?

Accepted Answer

Run from source using `npm run start` or from compiled JavaScript using `npm run start:dist`.

Question 6

What is Smithery.ai and how does GemForge-mcp integrate with it?

Accepted Answer

Smithery.ai is a platform for deploying AI tools. GemForge-mcp includes a `smithery.yaml` file for easy deployment and configuration on Smithery.ai.

Question 7

How do I deploy GemForge-mcp using Docker?

Accepted Answer

Build the Docker image using `docker build -t gemforge-mcp .` and run the container with the required environment variables, such as `GEMINI_API_KEY`.

Question 8

What are the available tools in GemForge-mcp?

Accepted Answer

GemForge-mcp provides four tools: `gemini_search`, `gemini_reason`, `gemini_code`, and `gemini_fileops` for various AI tasks.

Question 9

What does the `gemini_search` tool do?

Accepted Answer

The `gemini_search` tool generates responses based on the latest information using Gemini models with Google Search integration.

Question 10

How does the `gemini_reason` tool work?

Accepted Answer

The `gemini_reason` tool solves complex problems with step-by-step reasoning using advanced Gemini models.

Question 11

What is the purpose of the `gemini_code` tool?

Accepted Answer

The `gemini_code` tool analyzes codebases using Repomix and Gemini models to answer questions about code structure, logic, and potential improvements.

Question 12

What can I do with the `gemini_fileops` tool?

Accepted Answer

The `gemini_fileops` tool performs efficient operations on files (text, PDF, images, etc.) using appropriate Gemini models.

Question 13

How does GemForge-mcp handle model selection?

Accepted Answer

GemForge-mcp implements intelligent model selection based on task type (search, reasoning, etc.) and available models (FAST, BALANCED, ADVANCED, LARGE_CONTEXT).

Question 14

What are the special features of GemForge-mcp?

Accepted Answer

Special features include system instruction hoisting, XML content processing, file type detection, rate limiting handling, error recovery, custom Repomix options, and multi-file processing.

Question 15

How do I use multi-file analysis with `gemini_fileops`?

Accepted Answer

Pass an array of file paths to the `file_path` parameter in `gemini_fileops`, ensuring consistent file types and providing a specific `instruction` parameter.

Question 16

What environment variables are required for Docker deployment?

Accepted Answer

The required environment variables are `GEMINI_API_KEY`, `GEMINI_PAID_TIER` (optional), and `DEFAULT_MODEL_ID` (optional).

Question 17

How can I contribute to GemForge-mcp?

Accepted Answer

Fork the repository, create a feature branch, commit your changes, push to the branch, and open a Pull Request.

Question 18

Where can I find the license information?

Accepted Answer

The project is licensed under the MIT License. See the LICENSE file for details.

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