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Gomcptest
概述
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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 CompatibilitySupports the OpenAI v1 chat completion format for easy integration with existing tools
Google Gemini IntegrationUses VertexAI API to interact with Google's Gemini models
Streaming SupportProvides real-time streaming responses for better user experience
Function CallingAllows models to call external functions and incorporate results
MCP Tool IntegrationWorks with various MCP-compatible tools (Bash, File Editing, Grep, etc.)
Pros and Cons
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 PrerequisitesEnsure you have Go 1.21+ installed and GCP access configured
Build ToolsCompile all the necessary tools using the provided Makefile
Configure EnvironmentSet up required environment variables in .envrc
Start ServerRun the openaiserver to begin testing
Test with CLIUse the provided CLI to interact with the system
Example Use Cases
Code Security ScanningCreate an agent that scans code repositories for potential security vulnerabilities
Automated DocumentationGenerate comprehensive documentation from source code
Data AnalysisProcess and visualize complex datasets
Frequently Asked Questions
1
Is this production-ready?No, this is strictly a proof-of-concept for experimentation and learning purposes.
2
What safety precautions should I take?Always run in a container/chroot environment as the tools can execute commands and modify files.
3
Can I use models other than Gemini?Currently the implementation is specifically designed for Gemini through Vertex AI.
4
How do I add new tools?You can create new MCP-compatible tools by following the patterns in the existing tools directory.
Additional Resources
Project DocumentationAuto-generated project documentation
Google Vertex AIInformation about Google's Vertex AI service
Model Context ProtocolMCP protocol implementation
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