MCP 101: The Model Context Protocol for AI Agents
In this conversation, Jonny Daenen and Pierre Crochelet explore the Model Context Protocol (MCP), a framework that enhances AI assistants by allowing them to perform various tasks through tools, resources, and prompts.
They discuss the architecture of MCP, how to build an MCP server, and the developer flow for creating tools. The conversation also touches on the compatibility of MCP with different AI agents and the user experience, highlighting both the potential and limitations of the protocol.
They discuss the architecture of MCP, how to build an MCP server, and the developer flow for creating tools. The conversation also touches on the compatibility of MCP with different AI agents and the user experience, highlighting both the potential and limitations of the protocol.
Resources:
- Demo code: https://github.com/datamindedbe/demo-technology-exploration/tree/main/demos/claude_mcp
- MCP servers: https://github.com/modelcontextprotocol/servers
- MCP directory: https://mcp.so/
- Click here to watch a video of this episode.
- Full playlist: https://www.youtube.com/playlist?list=PLJ_da7qdfL80rA7byzC_CmyrfJWjcCTnb
Chapters:
- (00:00) - Introduction
- (01:03) - Demo: Claude Desktop & MCP
- (04:43) - What is the Model Context Protocol?
- (07:09) - Tools, Resources & Prompts
- (08:20) - The protocol: Host-Client-Server
- (11:05) - Building your own MCP server
- (16:46) - Prompts, resources & tool functionality
- (19:45) - Developer flow & the Inspector
- (23:31) - Function limitations & return types
- (26:34) - Testing the tool & integrating other agents
- (28:46) - Community MCP servers & current limitations
- (32:11) - Summary & next steps
Data & AI: Technology Explorations is a biweekly show from Dataminded. Each episode a Dataminded engineer demos a tool or technique worth knowing about -- working code, honest takes, no hype.
Music by Aleksandr Karabanov from Pixabay
