"Less" matching MCP servers:

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Acts as a proxy/router for multiple downstream MCP servers, exposing only meta-tools to the host to reduce token usage, enabling efficient search and invocation of tools from a fleet of servers.

A Model Context Protocol server that enables integration with the TESS API, allowing users to list and manage agents, execute agents with custom messages, and manage files through natural language interfaces.

A reference implementation of the mcp-lens pattern for progressive disclosure in MCP servers. It exposes three stable meta-tools to search, inspect, and execute capabilities, keeping tool-definition costs constant as the catalog grows.

A Model Context Protocol (MCP) server that provides persistent memory and context management for AI systems through a structured 5-phase optimization workflow.