Aggregates multiple Model Context Protocol servers into a single gateway to provide unified search, description, and execution of tools. It reduces context limit issues by dynamically fetching specific tool schemas only when needed rather than loading all available tools at once.
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.
MCP proxy that bundles flat tool lists into hierarchical subcommand groups to reduce context token usage, supporting multi-server aggregation and auto-generated help from tool schemas.
Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.
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.
A single MCP server that fronts many downstream MCP servers and Skills, exposing only four tools (search, call_tool, use_skill, admin) so that an agent's context window only ever sees search results on demand.
