Goose With MCP Servers
A Docker image project named Goose, integrated with the MCP server, supporting connection to LLM models through Ollama and adding GitHub MCP services via command - line extensions.
rating : 2.5 points
downloads : 6.4K
What is the Goose and MCP Server?
Goose is an AI assistant that connects to multiple language models. This Docker image is pre - configured with the Model Context Protocol (MCP) server, providing more context and features by extending Goose's capabilities.How to Use the Goose and MCP Server?
After setting up the Docker container, you need to configure Goose to connect to your preferred language model provider (such as Ollama) and add any MCP server extensions you want to use.Feature Highlights
By integrating the MCP server, users can obtain richer context information and functional support during interactions with Goose. For example, GitHub repository content can be directly referenced and manipulated in conversations.Main Features
Multi - Model Support
Compatible with any language model, including but not limited to models like qwen2.5 provided by Ollama.
MCP Protocol Integration
Extend functionality through the MCP server, providing more powerful context processing capabilities.
GitHub Integration
Supports direct referencing and manipulation of GitHub repository content, improving collaboration efficiency.
Advantages and Disadvantages Analysis
Advantages
Disadvantages
Usage Guide
Install and run the Docker environment.
Pull the Goose image and start the container.
Configure the MCP server and GitHub credentials.
Start and interact with Goose.
Usage Examples
Frequently Asked Questions
Why use host.docker.internal instead of localhost?
How to obtain a GitHub personal access token?
Which models does Goose support?
Additional Resources
Goose GitHub Repository
The official code repository for the Goose project.
Ollama Documentation
Detailed information about the Ollama language model provider.
GitHub Personal Access Token Guide
How to create and use a GitHub personal access token.

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