MCP, Context Model… Perfection?
summary
How to integrate DevOps tools (Grafana, Jira, GitHub, Postgres, etc.) with language models using the Model Context Protocol (MCP) so models can access relevant context instead of unused data. The workshop covers connecting dashboards, tickets and repositories, compares MCP communication mechanisms with respect to security and scalability, and shows how to wire MCP servers to MCP clients for end-to-end orchestration.
AI-written summary · about
chapters (8)
- 0:00MCP and context engineering
- 6:28MCP servers for integration
- 12:30MCP standard for AI tools
- 23:26Building MCP servers
- 33:43MCP with LLMs and IDEs
- 44:48Better tool descriptions and security
- 47:38Controlling tool access
- 51:12MCP in production
related talks
33mThe Model Context Protocol: Connecting AI to Everything
32mMCP for dummies: Feed more context to LLM
44mBeyond the Prompt: How MCP Connects Language Models to Real Tools
44mSupercharging DevOps with MCP (Without Opening a Security Hole)
42mMCP in Practice: One App to Understand It All
46mMCP for LLM Agents, Infrastructure APIs & Data Services
45mModel Context Protocol (MCP): The future of user interactions?
26mBuilding AI-Enabled Spring Applications with Model Context Protocol (MCP)
