MCP Course #7 - Config JSON with LangChain MCP Client, connect multiple servers
End-to-end MCP Course with code. Get the code here - MCP Client - https://theailanguage.com/onlySubscri..., MCP Server - https://theailanguage.com/onlySubscri...
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What you need to know from past videos -
MCP Course #6 - Build Docker MCP Server
• MCP Course #6 - Build Docker MCP Serv...
MCP Course #5 - Building Langchain MCP Client with Python, Google Gemini
• MCP Course #5 - Building Langchain MC...
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📺 A powerful LangChain-based MCP client that can load multiple servers from a config file and give Gemini access to all your external tools in one place!
By the end of this video, you'll be able to:
✅ Connect to multiple MCP servers using a JSON config
✅ Load and unify tools from all connected servers
✅ Use Google Gemini via LangChain's React Agent
✅ Interactively query Gemini and have it invoke MCP tools intelligently
✅ Extend or switch servers easily using the config file
📂 This client is perfect for scaling your AI workflows, giving Gemini access to rich, real-time external tools — without writing new integration code for every server!
🧰 Command to run this client:
uv run langchain_mcp_client_wconfig.py
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Chapters
00:00 Intro - what are we building?
00:59 Demo - config.json file
01:35 Demo - client working
05:47 Code Walkthrough - START
06:37 Note 1 - what you need to know from past videos
07:28 Code Walkthrough - CONT
08:46 Note 2 - Gemini Model Choice
09:44 Code Walkthrough - END
13:37 Setup Pre-existing Server
17:34 Outro
