Building RAG and MCP Servers with Claude

Edureka combines three connected implementation problems: exposing capabilities through MCP, retrieving useful context, and coordinating an agent workflow. Its roughly eight-hour syllabus suits someone who wants to see these pieces work together, rather than study the protocol in isolation. Retrieval lessons include chunking, embeddings and ranking.

What you will learn

• Design MCP tools and server integrations with controlled inputs.
• Assemble a retrieval pipeline and inspect how context is ranked.
• Trace planning and tool orchestration through an automated workflow.

Who this suits

Python users building a document assistant or a tool-driven prototype with Claude.

Before you enroll

The stated prerequisites are intermediate Python and familiarity with APIs or AI applications. A broad integration course leaves less time for each individual subsystem than a dedicated retrieval or protocol course.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Tool subscriptions, model API usage and cloud services may cost extra.

Put it into practice

Connect an MCP lookup tool to a small collection of public documents. Keep an evaluation set that distinguishes retrieval failures from incorrect tool arguments.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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