mcp-builder
Architectural guide and best practices for building robust Model Context Protocol servers.
Install
mkdir -p .claude/skills/mcp-builder-underundregh && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/12090" && unzip -o skill.zip -d .claude/skills/mcp-builder-underundregh && rm skill.zipInstalls to .claude/skills/mcp-builder-underundregh
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
MCP (Model Context Protocol) server building principles. Tool design, resource patterns, best practices.Key capabilities
- →Define tools as functions AI can call.
- →Implement resources as data AI can read.
- →Structure prompts using pre-defined templates.
- →Design tools with clear names, single purpose, validated input, and structured output.
- →Handle errors by returning structured messages without exposing internal details.
How it works
The skill outlines principles for building MCP servers, focusing on tool design, resource patterns, error handling, and security to create validated, schema-driven components.
Inputs & outputs
When to use mcp-builder
- →Design custom MCP tools
- →Structure resources for AI access
- →Implement server architecture
About this skill
MCP Builder
ultrathink
"Сисадмин но дзюцу!!!" — When the MCP server magically works on first try. "Человечек сориентирует." — MCP tools are sub-routines you wire up for the model.
Principles for building MCP servers.
1. MCP Overview
What is MCP?
Model Context Protocol - standard for connecting AI systems with external tools and data sources.
Core Concepts
| Concept | Purpose |
|---|---|
| Tools | Functions AI can call |
| Resources | Data AI can read |
| Prompts | Pre-defined prompt templates |
2. Server Architecture
Project Structure
my-mcp-server/
├── src/
│ └── index.ts # Main entry
├── package.json
└── tsconfig.json
Transport Types
| Type | Use |
|---|---|
| Stdio | Local, CLI-based |
| SSE | Web-based, streaming |
| WebSocket | Real-time, bidirectional |
3. Tool Design Principles
Good Tool Design
| Principle | Description |
|---|---|
| Clear name | Action-oriented (get_weather, create_user) |
| Single purpose | One thing well |
| Validated input | Schema with types and descriptions |
| Structured output | Predictable response format |
Input Schema Design
| Field | Required? |
|---|---|
| Type | Yes - object |
| Properties | Define each param |
| Required | List mandatory params |
| Description | Human-readable |
4. Resource Patterns
Resource Types
| Type | Use |
|---|---|
| Static | Fixed data (config, docs) |
| Dynamic | Generated on request |
| Template | URI with parameters |
URI Patterns
| Pattern | Example |
|---|---|
| Fixed | docs://readme |
| Parameterized | users://{userId} |
| Collection | files://project/* |
5. Error Handling
Error Types
| Situation | Response |
|---|---|
| Invalid params | Validation error message |
| Not found | Clear "not found" |
| Server error | Generic error, log details |
Best Practices
- Return structured errors
- Don't expose internal details
- Log for debugging
- Provide actionable messages
6. Multimodal Handling
Supported Types
| Type | Encoding |
|---|---|
| Text | Plain text |
| Images | Base64 + MIME type |
| Files | Base64 + MIME type |
7. Security Principles
Input Validation
- Validate all tool inputs
- Sanitize user-provided data
- Limit resource access
API Keys
- Use environment variables
- Don't log secrets
- Validate permissions
8. Configuration
Claude Desktop Config
| Field | Purpose |
|---|---|
| command | Executable to run |
| args | Command arguments |
| env | Environment variables |
9. Testing
Test Categories
| Type | Focus |
|---|---|
| Unit | Tool logic |
| Integration | Full server |
| Contract | Schema validation |
10. Best Practices Checklist
- Clear, action-oriented tool names
- Complete input schemas with descriptions
- Structured JSON output
- Error handling for all cases
- Input validation
- Environment-based configuration
- Logging for debugging
Remember: MCP tools should be simple, focused, and well-documented. The AI relies on descriptions to use them correctly.
When not to use it
- →When building a server that does not adhere to the Model Context Protocol (MCP).
- →When the user wants to expose internal server details in error messages.
- →When the user does not want to validate tool inputs.
Limitations
- →Focuses on Model Context Protocol (MCP) principles.
- →Requires input validation for all tool inputs.
- →Does not expose internal details in error responses.
How it compares
This skill provides a standardized framework for building AI-connected tools and data sources, ensuring consistency and predictability, unlike ad-hoc server development.
Compared to similar skills
mcp-builder side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| mcp-builder (this skill) | 0 | 2mo | No flags | Advanced |
| mcp-builder | 136 | 3mo | Review | Advanced |
| copilot-sdk | 7 | 4mo | Review | Intermediate |
| chatgpt-app-builder | 5 | 2mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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