Go-Mcp-Server
Go-Mcp-Server是一款code方向的AI技能，核心价值是Best practices and patterns for building Model Context Protocol (MCP) servers in Go using the official github，可用于解决开发者在code领域的实际问题，帮助用户提升效率、自动化重复任务或优化工作流。
Best practices and patterns for building Model Context Protocol (MCP) servers in Go using the official github.com/modelcontextprotocol/go-sdk package.
mkdir -p ./skills/go-mcp-server && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/go-mcp-server/SKILL.md -o ./skills/go-mcp-server/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Go MCP Server Development Guidelines
When building MCP servers in Go, follow these best practices and patterns using the official Go SDK.
Server Setup
Create an MCP server using `mcp.NewServer`:
import "github.com/modelcontextprotocol/go-sdk/mcp"
server := mcp.NewServer(
&mcp.Implementation{
Name: "my-server",
Version: "v1.0.0",
},
nil, // or provide mcp.Options
)Adding Tools
Use `mcp.AddTool` with struct-based input and output for type safety:
type ToolInput struct {
Query string `json:"query" jsonschema:"the search query"`
Limit int `json:"limit,omitempty" jsonschema:"maximum results to return"`
}
type ToolOutput struct {
Results []string `json:"results" jsonschema:"list of search results"`
Count int `json:"count" jsonschema:"number of results found"`
}
func SearchTool(ctx context.Context, req *mcp.CallToolRequest, input ToolInput) (
*mcp.CallToolResult,
ToolOutput,
error,
) {
// Implement tool logic
results := performSearch(ctx, input.Query, input.Limit)
return nil, ToolOutput{
Results: results,
Count: len(results),
}, nil
}
// Register the tool
mcp.AddTool(server,
&mcp.Tool{
Name: "search",
Description: "Search for information",
},
SearchTool,
)Adding Resources
Use `mcp.AddResource` for providing accessible data:
func GetResource(ctx context.Context, req *mcp.ReadResourceRequest) (*mcp.ReadResourceResult, error) {
content, err := loadResourceContent(ctx, req.URI)
if err != nil {
return nil, err
}
return &mcp.ReadResourceResult{
Contents: []any{
&mcp.TextResourceContents{
ResourceContents: mcp.ResourceContents{
URI: req.URI,
MIMEType: "text/plain",
},
Text: content,
},
},
}, nil
}
mcp.AddResource(server,
&mcp.Resource{
URI: "file:///data/example.txt",
Name: "Example Data",
Description: "Example resource data",
MIMEType: "text/plain",
},
GetResource,
)Adding Prompts
Use `mcp.AddPrompt` for reusable prompt templates:
type PromptInput struct {
Topic string `json:"topic" jsonschema:"the topic to analyze"`
}
func AnalyzePrompt(ctx context.Context, req *mcp.GetPromptRequest, input PromptInput) (
*mcp.GetPromptResult,
error,
) {
return &mcp.GetPromptResult{
Description: "Analyze the given topic",
Messages: []mcp.PromptMessage{
{
Role: mcp.RoleUser,
Content: mcp.TextContent{
Text: fmt.Sprintf("Analyze this topic: %s", input.Topic),
},
},
},
}, nil
}
mcp.AddPrompt(server,
&mcp.Prompt{
Name: "analyze",
Description: "Analyze a topic",
Arguments: []mcp.PromptArgument{
{
Name: "topic",
Description: "The topic to analyze",
Required: true,
},
},
},
AnalyzePrompt,
)Transport Configuration
Stdio Transport
For communication over stdin/stdout (most common for desktop integrations):
if err := server.Run(ctx, &mcp.StdioTransport{}); err != nil {
log.Fatal(err)
}HTTP Transport
For HTTP-based communication:
import "github.com/modelcontextprotocol/go-sdk/mcp"
transport := &mcp.HTTPTransport{
Addr: ":8080",
// Optional: configure TLS, timeouts, etc.
}
if err := server.Run(ctx, transport); err != nil {
log.Fatal(err)
}Error Handling
Always return proper errors and use context for cancellation:
func MyTool(ctx context.Context, req *mcp.CallToolRequest, input MyInput) (
*mcp.CallToolResult,
MyOutput,
error,
) {
// Check context cancellation
if ctx.Err() != n🎯 Best For
- UI designers
- Product designers
- Claude users
- GitHub Copilot users
- Software engineers
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Go-Mcp-Server to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
Is Go-Mcp-Server compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Go-Mcp-Server?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Go-Mcp-Server?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/go-mcp-server/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.