Build Agentic AIs with Python RAG and MCP training course

MCP server (capabilities as tools)

• MCP concepts: tool discovery, schemas, calling conventions
• Build a minimal MCP server in Python (hello tool → real tools)
• Implement 3–5 practical tools:

• • Filesystem (sandboxed), HTTP fetch (restricted), DB query (read-only), calculators, internal APIs

• Auth + permissions model (per-tool scopes), observability, versioning

Chatbot (the “front door”)

• Build a simple chat UI/CLI + API backend
• Streaming responses, tool call UX, citations/grounding display
• Session storage: in-memory → Redis/Postgres upgrade path

RAG fundamentals (grounded answers)

• Chunking, embeddings, vector stores (local first, then managed option)
• Retrieval strategies: hybrid search, metadata filters, reranking
• Prompting for grounded responses + citation linking
• RAG evaluation: recall/precision sanity checks, adversarial queries

Agent memory + workflows

• Short-term memory (session), long-term memory (user profile / notes)
• Summarisation, decay, and “don’t remember this” controls
• Workflow patterns: ReAct, plan-and-execute, toolformer-like routing

Exposing capabilities safely

• Capability design: input contracts, idempotency, side-effect isolation
• Human-in-the-loop approvals for risky tools
• Secrets management, policy checks, sandboxing, audit trails

Multi-agent systems

• When multi-agent helps vs hurts (latency/complexity tradeoffs)
• Roles: router, researcher, coder, critic, executor
• Coordination patterns: supervisor, swarm, debate, blackboard, task queue
• Shared context + shared tools; conflict resolution and consensus

Production concerns (as we harden the build)

• Tracing + structured logs, metrics, tool call timelines
• Reliability: retries, timeouts, circuit breakers, fallbacks
• Cost controls: caching, batching, model selection, token budgeting
• Deployment: containerise, run MCP + API, config per environment

Capstone project

• A full agentic app: chatbot + RAG + MCP tool suite + multi-agent workflow
• Demo scenarios, test suite, and “how to extend” checklist