Search

Purpose

Connect a Search MCP to an agent so it can search your platform for courses, programs, and agents—and return grounded, recommendation-ready results without hallucinations.

Overview

The Search MCP uses an MCP server (in this demo, ibl.ai’s own search MCP) to power an agent that acts as a search assistant. It can:

Search the course catalog (courses/programs).
Find and recommend agents.
Ask follow-up filters (subject, level, format, language).
Enforce guardrails via the system prompt.

Prerequisites

An agent with a Search Assistant system prompt.
MCP Tool enabled for the agent.
An API key for the Search MCP server.

Setup Steps

1) Prepare the Agent

Open the agent you want to use for search.
Set the system prompt to a search-focused assistant (catalog + agent search, recommendations, guardrails).

2) Enable the MCP Tool

Go to the agent’s Tools tab.
Ensure MCP is enabled.

3) Add the Search MCP Connector

Open the MCP tab.
Add (or edit) a connector with:
- Connector name
- Server location (Search MCP server URL)
- Description
  - Acts like instructions for the connection (what the agent can pull and how to respond).
- Transport: Streamable HTTP
- Authentication: API Key
  - Token type: API Key
  - Token value: paste your token
Save the connector.

Using Search in Chat

Search Courses

Prompt example:

“What courses are available on the platform?”

Result:

Returns a subset of courses from the tenant (even if the catalog is large).
Asks if you want to filter by subject, level, format, or language.

Search Agents

Prompt example:

“What agents can help me become a better user?”

Result:

Lists relevant agents (e.g., study tips, quizzes, Socratic support).
Offers to filter further or show more results (based on system-prompt limits).

Result

With Search MCP connected, agents can reliably discover courses and agents across your platform, guide users with filters and recommendations, and return accurate, grounded results from your own data.