Optimizes MCP tool menus from OpenAPI specs by grouping operations by tag and trimming schemas to reduce token usage, improving agent tool-selection accuracy.
A single MCP endpoint for AI agents to browse, inspect, and call tools from multiple upstream MCP servers without loading all schemas upfront, reducing context overhead.
Provides efficient knowledge-graph queries and unrestricted shell delegation for AI agents, reducing token usage by 80-150x and bypassing app tier restrictions.
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.