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Coursera

Trupeer MCP: From Knowledge Base to AI-Powered Workflows

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Overview

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Connect a Trupeer knowledge base to AI assistants and turn documented processes into workflows. You’ll learn how MCP links Claude, ChatGPT, and Cursor with Trupeer while keeping source quality, access, and review in view. Throughout the course, you’ll explore: MCP Foundations: Understand hosts, clients, servers, tools, and Trupeer’s role through the universal-adapter analogy. AI-Ready Knowledge Bases: Prioritize processes, record tutorials and SOPs, build a Trupeer knowledge base, and use AI Search. Secure Connections: Connect Trupeer to Claude through MCP, compare MCP with built-in search, manage authentication, and troubleshoot access. Reliable Querying: Write clear questions, retrieve sourced answers, build plans or checklists, and improve reliability. Business Use Cases: Design assistants for onboarding, customer support, and sales using persona, trigger, prompt, and handoff. Creation and Improvement: Generate presentations, help content, quizzes, and documentation reviews, then check outputs against sources. By the end, you’ll be able to connect Trupeer to an AI assistant, create useful materials from documented knowledge, identify content gaps, and plan team adoption.

Syllabus

  • Introduction to MCP and AI-Powered Knowledge
    • This module introduces MCP, the open standard that lets an AI assistant such as Claude or ChatGPT connect to outside tools and services. Using a plain "universal adapter" analogy, it explains what MCP is, how the parts of a connection fit together, and what an assistant can and can't do once connected. It also shows where Trupeer fits as a service an assistant can connect to, with a first look at Trupeer working inside Claude.
  • Building an AI-Ready Knowledge Base with Trupeer
    • This module covers how to build a knowledge base in Trupeer that is ready to be used with AI. It explains why an assistant's answers can only be as good as the content behind them, how to decide what to document first, and how to create that content by recording a process in Trupeer and letting it generate the guide rather than writing from scratch. It also covers adding content to a Trupeer knowledge base and using Trupeer's built-in AI search.
  • Connecting Trupeer to AI Through MCP
    • This module covers how to connect a Trupeer knowledge base to an AI assistant through MCP. It explains how the MCP connection differs from Trupeer's built-in AI search, how to prepare a knowledge base before connecting, and how to connect Trupeer to Claude step by step, with notes on other assistants such as ChatGPT and Cursor. It also covers how sign-in and access keep your content secure, and how to test the connection and fix common problems.
  • Querying, Prompting & Building from Your Knowledge
    • This module covers how to ask an AI assistant questions that draw reliable answers from a connected Trupeer knowledge base. It explains how an assistant decides when to look in the knowledge base, what a well-phrased question looks like, and how the wording of a request shapes the result. It also shows how to go beyond simple lookups by using what the assistant retrieves as material to build something new, and how to keep answers accurate.
  • Real-World Business Use Cases
    • This module covers how specific teams can use an AI assistant connected to Trupeer in their daily work. It introduces a simple way to design a knowledge assistant around who is asking, what prompts the question, how it's phrased, and where the answer goes next, then applies that approach to onboarding, customer support, and sales. It also provides ready-to-use prompts organised by team.
  • Creating & Optimizing with Your Knowledge
    • This module covers how to create new material from content already in a Trupeer knowledge base, and how to improve the knowledge base itself. It shows how to generate a presentation, help content, and a quiz from existing Trupeer content using an AI assistant, how to check that generated material against its sources, and how to use the assistant to review documentation, spotting unclear steps and finding gaps that real questions reveal.
  • Conclusion & Assessment
    • This module covers how to tell whether a Trupeer MCP connection is helping a team and how to encourage adoption. It looks at practical ways to measure success, then follows a single scenario, a documented process changing, through the whole workflow from updating the content in Trupeer to answering and building from it in an AI assistant. It closes with a final assessment and suggestions for next steps.

Taught by

Anton Voroniuk

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