How does this skill reduce token usage so significantly?

Traditional MCP usage requires tool definitions to be passed in every prompt. This skill converts those definitions into a code library that the agent explores via the filesystem, loading only the necessary types and logic for the specific task at hand.

Does this require a specialized execution environment?

This skill is best used in environments where the AI agent has the ability to execute TypeScript/JavaScript code, such as the Claude Code CLI or a sandboxed runtime.

Can I use this with existing MCP servers?

Yes, this pattern is designed to wrap any standard MCP server. It provides templates to analyze existing tools and generate the corresponding TypeScript interfaces and modules automatically.

What are the security benefits of this approach?

By keeping intermediate data (like PII) within the code execution environment rather than passing it back and forth to the model, you reduce the exposure of sensitive data while maintaining functionality.

MCP Tools as Code

Name: MCP Tools as Code
Author: cameronsjo

bycameronsjo

•

API開発

Transforms MCP servers into typed TypeScript APIs to drastically reduce token usage and enable programmatic control flow.

概要

MCP Tools as Code provides a structured framework for converting discrete Model Context Protocol (MCP) tool calls into a unified, typed TypeScript library. By exposing MCP servers as code modules rather than context-heavy tool definitions, this skill allows AI agents to interact with external services with over 98% fewer tokens. It is an essential pattern for developers building sophisticated agents that manage complex workflows across multiple platforms, requiring native error handling, loops, and efficient data filtering within limited context windows.

主な機能

Automatic TypeScript type generation from MCP JSON schemas
Secure transport layer for efficient, sandboxed code execution
Native control flow support including loops and try/catch blocks
1 GitHub stars
Token usage reduction (98%+) via programmatic tool access
Progressive disclosure to load tool definitions only when required

ユースケース

Processing high-volume datasets where intermediate results remain in the sandbox
Optimizing cost-sensitive AI agent deployments by minimizing prompt overhead
Orchestrating complex multi-step workflows across diverse enterprise platforms

概要

主な機能

Automatic TypeScript type generation from MCP JSON schemas
Secure transport layer for efficient, sandboxed code execution
Native control flow support including loops and try/catch blocks
1 GitHub stars
Token usage reduction (98%+) via programmatic tool access
Progressive disclosure to load tool definitions only when required

ユースケース

Processing high-volume datasets where intermediate results remain in the sandbox
Optimizing cost-sensitive AI agent deployments by minimizing prompt overhead
Orchestrating complex multi-step workflows across diverse enterprise platforms