Consolidates code understanding, documentation, browser automation, memory, and knowledge graph into a single MCP server with progressive discovery for up to 98% token reduction.
Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON
Token-efficient MCP reimplementation with progressive tool discovery, result handling, and compact wire encoding, reducing token usage by up to 89% on tool definitions.
Unified MCP orchestration layer that consolidates multiple MCPs into a single interface with semantic tool discovery, code-mode execution, scheduling, and intelligent caching to reduce token usage by 97% and eliminate choice paralysis.