mcp-server-patterns▌
affaan-m/everything-claude-code · updated Apr 8, 2026
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The Model Context Protocol (MCP) lets AI assistants call tools, read resources, and use prompts from your server. Use this skill when building or maintaining MCP servers. The SDK API evolves; check Context7 (query-docs for "MCP") or the official MCP documentation for current method names and signatures.
MCP Server Patterns
The Model Context Protocol (MCP) lets AI assistants call tools, read resources, and use prompts from your server. Use this skill when building or maintaining MCP servers. The SDK API evolves; check Context7 (query-docs for "MCP") or the official MCP documentation for current method names and signatures.
For the broader routing decision of when a capability should be a rule, a skill, MCP, or a plain CLI/API workflow, see docs/capability-surface-selection.md.
When to Use
Use when: implementing a new MCP server, adding tools or resources, choosing stdio vs HTTP, upgrading the SDK, or debugging MCP registration and transport issues.
How It Works
Core concepts
- Tools: Actions the model can invoke (e.g. search, run a command). Register with
registerTool()ortool()depending on SDK version. - Resources: Read-only data the model can fetch (e.g. file contents, API responses). Register with
registerResource()orresource(). Handlers typically receive auriargument. - Prompts: Reusable, parameterised prompt templates the client can surface (e.g. in Claude Desktop). Register with
registerPrompt()or equivalent. - Transport: stdio for local clients (e.g. Claude Desktop); Streamable HTTP is preferred for remote (Cursor, cloud). Legacy HTTP/SSE is for backward compatibility.
The Node/TypeScript SDK may expose tool() / resource() or registerTool() / registerResource(); the official SDK has changed over time. Always verify against the current MCP docs or Context7.
Connecting with stdio
For local clients, create a stdio transport and pass it to your server’s connect method. The exact API varies by SDK version (e.g. constructor vs factory). See the official MCP documentation or query Context7 for "MCP stdio server" for the current pattern.
Keep server logic (tools + resources) independent of transport so you can plug in stdio or HTTP in the entrypoint.
Remote (Streamable HTTP)
For Cursor, cloud, or other remote clients, use Streamable HTTP (single MCP HTTP endpoint per current spec). Support legacy HTTP/SSE only when backward compatibility is required.
Examples
Install and server setup
npm install @modelcontextprotocol/sdk zod
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { z } from "zod";
const server = new McpServer({ name: "my-server", version: "1.0.0" });
Register tools and resources using the API your SDK version provides: some versions use server.tool(name, description, schema, handler) (positional args), others use server.tool({ name, description, inputSchema }, handler) or registerTool(). Same for resources — include a uri in the handler when the API provides it. Check the official MCP docs or Context7 for the current @modelcontextprotocol/sdk signatures to avoid copy-paste errors.
Use Zod (or the SDK’s preferred schema format) for input validation.
Best Practices
- Schema first: Define input schemas for every tool; document parameters and return shape.
- Errors: Return structured errors or messages the model can interpret; avoid raw stack traces.
- Idempotency: Prefer idempotent tools where possible so retries are safe.
- Rate and cost: For tools that call external APIs, consider rate limits and cost; document in the tool description.
- Versioning: Pin SDK version in package.json; check release notes when upgrading.
Official SDKs and Docs
- JavaScript/TypeScript:
@modelcontextprotocol/sdk(npm). Use Context7 with library name "MCP" for current registration and transport patterns. - Go: Official Go SDK on GitHub (
modelcontextprotocol/go-sdk). - C#: Official C# SDK for .NET.
How to use mcp-server-patterns on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add mcp-server-patterns
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches mcp-server-patterns from GitHub repository affaan-m/everything-claude-code and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate mcp-server-patterns. Access the skill through slash commands (e.g., /mcp-server-patterns) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★74 reviews- ★★★★★Mateo Menon· Dec 28, 2024
Useful defaults in mcp-server-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Xiao Torres· Dec 28, 2024
Solid pick for teams standardizing on skills: mcp-server-patterns is focused, and the summary matches what you get after install.
- ★★★★★Li Chen· Dec 28, 2024
Keeps context tight: mcp-server-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Zaid Shah· Dec 24, 2024
I recommend mcp-server-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ganesh Mohane· Dec 20, 2024
We added mcp-server-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Advait Harris· Dec 8, 2024
Registry listing for mcp-server-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Harper Chen· Dec 4, 2024
We added mcp-server-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Zaid Sharma· Nov 27, 2024
mcp-server-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Advait Martinez· Nov 19, 2024
I recommend mcp-server-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Chen Gupta· Nov 19, 2024
mcp-server-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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