Swift-Mcp-Server
Swift-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 Swift using the official MCP Swift SDK package，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 Swift using the official MCP Swift SDK package.
mkdir -p ./skills/swift-mcp-server && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/swift-mcp-server/SKILL.md -o ./skills/swift-mcp-server/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Swift MCP Server Development Guidelines
When building MCP servers in Swift, follow these best practices and patterns using the official Swift SDK.
Server Setup
Create an MCP server using the `Server` class with capabilities:
import MCP
let server = Server(
name: "MyServer",
version: "1.0.0",
capabilities: .init(
prompts: .init(listChanged: true),
resources: .init(subscribe: true, listChanged: true),
tools: .init(listChanged: true)
)
)Adding Tools
Use `withMethodHandler` to register tool handlers:
// Register tool list handler
await server.withMethodHandler(ListTools.self) { _ in
let tools = [
Tool(
name: "search",
description: "Search for information",
inputSchema: .object([
"properties": .object([
"query": .string("Search query"),
"limit": .number("Maximum results")
]),
"required": .array([.string("query")])
])
)
]
return .init(tools: tools)
}
// Register tool call handler
await server.withMethodHandler(CallTool.self) { params in
switch params.name {
case "search":
let query = params.arguments?["query"]?.stringValue ?? ""
let limit = params.arguments?["limit"]?.intValue ?? 10
// Perform search
let results = performSearch(query: query, limit: limit)
return .init(
content: [.text("Found \(results.count) results")],
isError: false
)
default:
return .init(
content: [.text("Unknown tool")],
isError: true
)
}
}Adding Resources
Implement resource handlers for data access:
// Register resource list handler
await server.withMethodHandler(ListResources.self) { params in
let resources = [
Resource(
name: "Data File",
uri: "resource://data/example.txt",
description: "Example data file",
mimeType: "text/plain"
)
]
return .init(resources: resources, nextCursor: nil)
}
// Register resource read handler
await server.withMethodHandler(ReadResource.self) { params in
switch params.uri {
case "resource://data/example.txt":
let content = loadResourceContent(uri: params.uri)
return .init(contents: [
Resource.Content.text(
content,
uri: params.uri,
mimeType: "text/plain"
)
])
default:
throw MCPError.invalidParams("Unknown resource URI: \(params.uri)")
}
}
// Register resource subscribe handler
await server.withMethodHandler(ResourceSubscribe.self) { params in
// Track subscription for notifications
subscriptions.insert(params.uri)
print("Client subscribed to \(params.uri)")
return .init()
}Adding Prompts
Implement prompt handlers for templated conversations:
// Register prompt list handler
await server.withMethodHandler(ListPrompts.self) { params in
let prompts = [
Prompt(
name: "analyze",
description: "Analyze a topic",
arguments: [
.init(name: "topic", description: "Topic to analyze", required: true),
.init(name: "depth", description: "Analysis depth", required: false)
]
)
]
return .init(prompts: prompts, nextCursor: nil)
}
// Register prompt get handler
await server.withMethodHandler(GetPrompt.self) { params in
switch params.name {
case "analyze":
let topic = params.arguments?["topic"]?.stringValue ?? "general"
let depth = params.arguments?["depth"]?.stringValue ?? "basic"
let description = "Analysis of \(topic) at \(depth) level"
let messages: [Prompt.Message] = [
.user("Please analyze this topic: \(topic)"),
.assist🎯 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 Swift-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 Swift-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 Swift-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 Swift-Mcp-Server?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/swift-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.