بنقرة واحدة
mcp-builder
MCP (Model Context Protocol) server building principles. Tool design, resource patterns, best practices.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
MCP (Model Context Protocol) server building principles. Tool design, resource patterns, best practices.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Token-efficient code review using Tree-sitter AST graphs and MCP. Reduces AI assistant token usage by 6.8–49x by computing blast radius of changes instead of reading entire codebases. Uses SQLite graph database for structural analysis.
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Socratic questioning protocol + user communication. MANDATORY for complex requests, new features, or unclear requirements. Includes progress reporting and error handling.
| name | mcp-builder |
| description | MCP (Model Context Protocol) server building principles. Tool design, resource patterns, best practices. |
| when_to_use | When building MCP (Model Context Protocol) servers, designing MCP tools, or implementing MCP resource patterns. |
| allowed-tools | Read, Write, Edit, Glob, Grep |
Principles for building MCP servers.
Model Context Protocol - standard for connecting AI systems with external tools and data sources.
| Concept | Purpose |
|---|---|
| Tools | Functions AI can call |
| Resources | Data AI can read |
| Prompts | Pre-defined prompt templates |
my-mcp-server/
├── src/
│ └── index.ts # Main entry
├── package.json
└── tsconfig.json
| Type | Use |
|---|---|
| Stdio | Local, CLI-based |
| SSE | Web-based, streaming |
| WebSocket | Real-time, bidirectional |
| 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 |
| Field | Required? |
|---|---|
| Type | Yes - object |
| Properties | Define each param |
| Required | List mandatory params |
| Description | Human-readable |
| Type | Use |
|---|---|
| Static | Fixed data (config, docs) |
| Dynamic | Generated on request |
| Template | URI with parameters |
| Pattern | Example |
|---|---|
| Fixed | docs://readme |
| Parameterized | users://{userId} |
| Collection | files://project/* |
| Situation | Response |
|---|---|
| Invalid params | Validation error message |
| Not found | Clear "not found" |
| Server error | Generic error, log details |
| Type | Encoding |
|---|---|
| Text | Plain text |
| Images | Base64 + MIME type |
| Files | Base64 + MIME type |
| Field | Purpose |
|---|---|
| command | Executable to run |
| args | Command arguments |
| env | Environment variables |
| Type | Focus |
|---|---|
| Unit | Tool logic |
| Integration | Full server |
| Contract | Schema validation |
Remember: MCP tools should be simple, focused, and well-documented. The AI relies on descriptions to use them correctly.