An MCP server that enables AI agents to execute sandboxed JavaScript and TypeScript code instead of calling individual tools directly. It significantly reduces token usage by allowing agents to filter, aggregate, and transform data locally before returning results.
Universal MCP server for executing TypeScript and Python code with progressive disclosure, reducing token usage by 98% by enabling on-demand access to all other MCP tools through code execution rather than loading tool definitions directly.
Enables LLMs to interact with MCP servers by writing TypeScript/JavaScript code instead of direct tool calls. Provides a code execution sandbox that accesses MCP servers through HTTP proxy endpoints.
A TypeScript-based server that allows calling other MCP clients from your own MCP client, facilitating task delegation and context window offloading for enhanced multi-agent interactions.
A production-grade TypeScript MCP server that provides AI agents with structured access to real-world data across financial markets, Web3/DeFi, developer tools, and healthcare domains. It features built-in authentication, domain isolation, caching, and rate limiting for reliable API integrations.
