From APIs to Agents: Enterprise AI using Java, Ollama & MCP
summary
A Java Spring Boot agent orchestrates Ollama LLM via an MCP client/server, exposing five concrete tools — create, read, update, delete, list — backed by a JSON file instead of a database; the demo uses Quen 2.5 (Alibaba) and runs locally but needs ~20 GB RAM to respond quickly, while 4–5 GB struggles. Security, auth, logging, retries and treating model calls as untrusted are enforced; Ollama runs locally and MCP bridges LLM and enterprise.
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chapters (8)
- 0:00Enterprise AI with Java & agents
- 3:41Agentic apps vs traditional APIs
- 7:55Java in AI agent orchestration
- 10:47Ollama for local LLM deployment
- 13:32Challenges and mitigation for local LLMs
- 16:42Model Context Protocol
- 18:14Demo: employee agent setup
- 25:06Live demo: agentic employee management
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