- Home
- Skills
- Vudovn
- Antigravity Kit
- Mcp Builder
mcp-builder_skill
- TypeScript
5.7k
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill vudovn/antigravity-kit --skill mcp-builder- SKILL.md3.2 KB
Overview
This skill explains principles for building MCP (Model Context Protocol) servers, focusing on tool design, resource patterns, error handling, security, and testing. It condenses architecture guidance and practical patterns for TypeScript-based MCP servers. The guidance emphasizes clarity, schema-driven inputs, and predictable outputs to make tools reliably usable by AI systems.
How this skill works
The skill inspects core MCP concepts: tools (callable functions), resources (readable data URIs), and prompts (templates). It lays out server transport options (stdio, SSE, WebSocket), recommended project layout, input/output schema conventions, and resource URI patterns. It also covers error handling, multimodal payload encoding, configuration, security measures, and testing strategies.
When to use it
- Designing a new MCP server or refactoring an existing one
- Defining tools and input/output schemas for AI integrations
- Choosing transport and resource URI patterns for clients
- Implementing secure input validation and secret handling
- Establishing testing and contract validation for MCP endpoints
Best practices
- Name tools with clear, action-oriented verbs and give each tool one focused responsibility
- Define complete input schemas: types, required fields, and human descriptions
- Return structured, predictable JSON outputs and document response shape
- Validate and sanitize all inputs; never log secrets or internal details
- Use environment variables for sensitive config and limit resource access by permissions
- Log actionable errors for debugging and return safe, user-facing messages
Example use cases
- Create a get_weather tool with a validated location schema and structured forecast output
- Serve project documents via URIs like docs://readme and parameterized URIs like users://{userId}
- Stream model responses to web clients over SSE or support interactive sessions over WebSocket
- Expose image and file resources as Base64 with MIME type metadata for multimodal tools
- Run unit, integration, and contract tests to ensure schemas and transports behave as expected
FAQ
Use stdio for local CLI tools, SSE for one-way streaming to web clients, and WebSocket for real-time bidirectional interactions.
How should I structure errors returned to the model?
Return structured error objects with type, message, and actionable details; log full diagnostics internally but avoid leaking sensitive internals.
How do I encode images and files for MCP?
Encode binary payloads as Base64 and include the MIME type and optional filename in the resource metadata.