An MCP server that exposes 43 domain tools behind 4 meta-tools, applying guardrails such as budgets, rate limits, schema validation, human-in-the-loop confirmation for mutations, PII redaction, and an append-only audit log while reducing context window usage.
A production-style MCP gateway that aggregates multiple tool servers into one surface with semantic tool search, RBAC, audit logging, and rate limiting, enabling efficient tool selection for AI agents.
A universal gateway that aggregates multiple MCP servers into a single interface while providing advanced token optimization, result filtering, and automated summarization. It enables efficient management of large tool catalogs and reduces context usage by up to 95% for major AI clients.
An enterprise MCP server that exposes 16 standardized tools for document intelligence, RAG, knowledge graph, SQL analysis, LLM evaluation, cost estimation, and AI architecture design, enabling AI agents to securely access and compose enterprise AI capabilities.
A multiplexing gateway that aggregates multiple MCP servers into a single port, significantly reducing context token usage through a Meta-MCP discovery system. It enables dynamic tool discovery and invocation across various transport protocols including stdio, HTTP, and SSE.
A local MCP gateway that compresses multiple upstream servers into two tools, search and execute, to minimize model context usage. It provides a compact, code-driven interface for discovering and calling tools across various upstream sources on demand.
