Pearl MCP Server Overview

Pearl’s Model Context Protocol (MCP) server bridges the gap between AI assistants and real‑world expertise. By exposing Pearl’s advanced AI engines and a network of vetted human experts through a single, standard interface, it enables developers to build hybrid conversational experiences that combine instant automation with authoritative human guidance. The server is designed for teams that need to scale AI interactions while retaining the ability to defer complex or sensitive queries to specialists, all without managing separate integrations for each service.

The server offers a rich set of interaction modes. AI‑only delivers rapid, fully automated responses for everyday questions, freeing human experts to focus on higher‑value tasks. AI‑Expert couples the speed of AI with a human expert’s review, ensuring accuracy for moderately critical topics. Finally, Expert mode routes the entire conversation to a live specialist, providing definitive answers for highly technical, legal, or medical inquiries. These modes are exposed as distinct tools (, , and ), allowing client applications to choose the appropriate level of intervention programmatically.

Key capabilities include session management, conversation history tracking, and support for both standard input/output (stdio) and Server‑Sent Events (SSE) transports. Session identifiers enable continuous, stateful dialogues that can span multiple turns or even persist across restarts. The history APIs ( and ) give developers visibility into past interactions, which is essential for compliance, auditability, and improving downstream AI models. The server’s transport flexibility ensures compatibility with a wide range of MCP‑compatible clients—from desktop assistants like Claude to web‑based tools such as Cursor.

Real‑world use cases abound. A healthcare SaaS can offer patients instant symptom triage via AI, then automatically hand off to a licensed medical professional when the query escalates. A legal tech platform can provide preliminary contract reviews with AI, flagging complex clauses for a human lawyer. In education, an e‑learning app might use AI to answer routine questions while routing academic advising or career counseling to qualified experts. The server’s expert categories—spanning medical, legal, technical, educational, and lifestyle domains—are automatically matched to query context, eliminating the need for manual routing logic.

Integration is straightforward: developers add Pearl’s MCP endpoint to their client’s tool list and invoke the desired tool with a JSON payload. The server handles authentication via an API key, communicates over HTTP or SSE, and returns structured responses that can be embedded directly into chat interfaces. Because the entire interaction flow is defined by MCP, teams can swap out or augment backend services without changing client code. This modularity makes Pearl’s MCP server a powerful backbone for any application that requires a blend of AI automation and trusted human expertise.