gomcptest: Proof of Concept for MCP with Custom Host

This project is a proof of concept (POC) demonstrating how to implement a Model Context Protocol (MCP) with a custom-built host. The code is primarily written from scratch to provide a clear understanding of the underlying mechanisms.

Project Structure

• host/openaiserver: Implements a custom host that mimics the OpenAI API, using Google Gemini and function calling. This is the core of the POC.
• tools: Contains various MCP-compatible tools that can be used with the host:
  • Bash: Execute bash commands
  • Edit: Edit file contents
  • GlobTool: Find files matching glob patterns
  • GrepTool: Search file contents with regular expressions
  • LS: List directory contents
  • Replace: Replace entire file contents
  • View: View file contents

Components

Key Features

• OpenAI Compatibility: The API is designed to be compatible with the OpenAI v1 chat completion format.
• Google Gemini Integration: It utilizes the VertexAI API to interact with Google Gemini models.
• Streaming Support: The server supports streaming responses.
• Function Calling: Allows Gemini to call external functions and incorporate their results into chat responses.
• MCP Server Interaction: Demonstrates interaction with a hypothetical MCP (Model Control Plane) server for tool execution.
• Single Chat Session: The application uses single chat session, and new conversation will not trigger a new session.

Quickstart

This guide will help you quickly run the openaiserver located in the host/openaiserver directory.

Prerequisites

• Go installed and configured.
• Environment variables properly set.

Running the Server

1. Navigate to the host/openaiserver directory:

   cd host/openaiserver
   

           2.  Set the required environment variables.  Refer to the Configuration section for details on the environment variables.  A minimal example:
   

   export IMAGE_DIR=/path/to/your/image/directory
   export GCP_PROJECT=your-gcp-project-id
   export IMAGE_DIR=/tmp/images # Directory must exist
   

2. Run the server:

   go run .
   

   or

   go run main.go
   

The server will start and listen on the configured port (default: 8080).

Configuration

The openaiserver application is configured using environment variables. The following variables are supported:

Global Configuration

Variable	Description	Default	Required
PORT	The port the server listens on	8080	No
LOG_LEVEL	Log level (DEBUG, INFO, WARN, ERROR)	INFO	No
IMAGE_DIR	Directory to store images		Yes

GCP Configuration

Variable	Description	Default	Required
GCP_PROJECT	Google Cloud Project ID		Yes
GEMINI_MODELS	Comma-separated list of Gemini models	gemini-1.5-pro,gemini-2.0-flash	No
GCP_REGION	Google Cloud Region	us-central1	No
IMAGEN_MODELS	Comma-separated list of Imagen models		No
IMAGE_DIR	Directory to store images		Yes
PORT	The port the server listens on	8080	No

Prerequisites

• Go >= 1.21
• github.com/mark3labs/mcp-go

Tools

            This repository includes several MCP-compatible tools that can be installed individually:

Installing Tools

You can install the tools from the releases page or build them from source.

From Releases

Download the appropriate release for your platform from the releases page.

Build from Source

To build all tools from source:

# Navigate to the tools directory
cd tools

# Build all tools
make all

# Or build individual tools
make Bash
make Edit
make GlobTool
make GrepTool
make LS
make Replace
make View

The built binaries will be available in the tools/bin directory.

Notes

• This is a POC and has limitations.
• The code is provided as is for educational purposes to understand how to implement MCP with a custom host.