Search files and code snippets using natural language queries, filter by path, similarity threshold, and result limit, and generate embeddings with customizable AI providers.
Convert natural language descriptions into Zig code for efficient development. The tool accepts prompts and context, enabling precise code generation tailored to specific requirements within the Zig MCP Server environment.
Enables efficient AI agent operations through sandboxed Python code execution with progressive tool discovery, PII tokenization, and skills persistence, achieving up to 98.7% token reduction by processing data in a sandbox rather than in context.
Executes Python code in isolated rootless containers while proxying MCP server tools, reducing context overhead by 95%+ and enabling complex multi-tool workflows through sandboxed code execution.
Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.