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Gomcptest

This project is a proof-of-concept (POC) that demonstrates how to implement the Model Context Protocol (MCP) through a custom host for testing agentic systems. Core features include OpenAI-compatible API, Google Gemini integration, streaming response support, and tool invocation capabilities.
Developer toolsArtificial intelligence chatbots#Model Protocol#Agentic System#Gemini Integration#Tool Invocation.Go
2.5 points
8.5K
Open Site

Overview

Content Details

Alternatives

What is gomcptest?

gomcptest is an experimental platform that allows developers to test and prototype agentic systems using the Model Context Protocol (MCP). It provides a custom-built host that mimics the OpenAI API while actually using Google's Gemini models through Vertex AI.

How to use gomcptest?

The system consists of a custom host server and various tools that can be combined to create specialized agents. You can build the tools, configure the environment, and then interact with them through the CLI or API interface.

Use Cases

Ideal for developing and testing specialized AI agents for code scanning, security analysis, automated documentation, data processing, and other developer productivity tools.

Key Features

OpenAI API Compatibility
Supports the OpenAI v1 chat completion format for easy integration with existing tools
Google Gemini Integration
Uses VertexAI API to interact with Google's Gemini models
Streaming Support
Provides real-time streaming responses for better user experience
Function Calling
Allows models to call external functions and incorporate results
MCP Tool Integration
Works with various MCP-compatible tools (Bash, File Editing, Grep, etc.)
Advantages
Flexible testing environment for agentic systems
OpenAI-compatible API makes integration easy
Supports multiple powerful tools out of the box
Streaming responses enable real-time interaction
Limitations
Proof-of-concept quality (not production-ready)
Requires Google Cloud Platform access
Potential security risks from tool execution
Limited documentation as an experimental project

Getting Started

Install Prerequisites
Ensure you have Go 1.21+ installed and GCP access configured
Build Tools
Compile all the necessary tools using the provided Makefile
Configure Environment
Set up required environment variables in .envrc
Start Server
Run the openaiserver to begin testing
Test with CLI
Use the provided CLI to interact with the system

Example Use Cases

Code Security Scanning
Create an agent that scans code repositories for potential security vulnerabilities
Automated Documentation
Generate comprehensive documentation from source code
Data Analysis
Process and visualize complex datasets

Frequently Asked Questions

Is this production-ready?
What safety precautions should I take?
Can I use models other than Gemini?
How do I add new tools?

Additional Resources

Project Documentation
Auto-generated project documentation
Google Vertex AI
Information about Google's Vertex AI service
Model Context Protocol
MCP protocol implementation

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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