Limitless AI MCP Server

The Limitless AI MCP Server is a beta‑grade bridge that lets AI assistants—such as Claude, Cursor, or Windsurf—to tap directly into a user’s Limitless AI Pendant recordings. By exposing the full Limitless API through the Model Context Protocol, developers can treat audio and transcription data as first‑class resources that AI tools can search, retrieve, and analyze on demand. This eliminates the need for custom integrations or manual data pipelines, enabling a truly conversational workflow where an assistant can answer questions about past sessions, pull out key moments, or generate summaries without leaving the chat.

At its core, the server implements all standard MCP components: tools, resources, prompts, and sampling. The five specialized tools cover common operations—searching by keyword, listing recordings within a date range, retrieving the most recent entries, fetching markdown content, and accessing metadata. Resources are presented as navigable URIs that reflect the hierarchical structure of a user’s recordings, making it easy for clients to explore content. Pre‑built prompts provide ready‑made templates for tasks like “summarize this session” or “extract action items,” while the sampling feature offers AI‑powered content analysis that can be invoked directly from a conversation. The discovery mechanism automatically registers these capabilities with any MCP‑compatible client, so users experience a seamless plug‑and‑play experience.

Key technical advantages include intelligent caching (LRU eviction with configurable TTLs) that keeps latency low even for large datasets, robust error handling with retry logic and timeout controls, and full TypeScript support that guarantees type safety across the stack. The server is intentionally lightweight—requiring only Node.js 22+ and a valid Limitless API key—yet it scales to accommodate thousands of recordings thanks to its modular architecture and efficient HTTP client.

Real‑world use cases abound. A team leader could ask the assistant to “show me all recordings from last week that mention budget,” and instantly receive a curated list with timestamps. A researcher might request “summarize the key points from today’s session,” and receive a concise markdown output. In product development, an AI can surface user feedback from recorded interviews by searching for specific pain points and then trigger follow‑up actions. Because the MCP server exposes recordings as resources, developers can also embed them in other tools—such as knowledge bases or analytics dashboards—without duplicating data.

In summary, the Limitless AI MCP Server turns passive audio archives into active conversational assets. By providing a standardized protocol interface, it empowers developers to build richer AI experiences that can read, search, and interpret user recordings on the fly, all while keeping performance high and integration effort minimal.