Understanding MCP From Scratch

LangChain · Intermediate ·🧠 Large Language Models ·1y ago
The Model Context Protocol (MCP) is an open standardized protocol that connects AI models with various data sources and tools. It functions like a "USB-C port for AI applications," allowing LLMs to seamlessly interact with local files, databases, APIs, and custom tools. But, it can be challenging to understand. Here, we breakdown how MCP works, build an MCP server for LangGraph docs from scratch, and connect it to Claude, Cursor, and Windsurf. Video notes: https://mirror-feeling-d80.notion.site/MCP-From-Scratch-1b9808527b178040b5baf83a991ed3b2?pvs=4 Learn how to build agents on LangChain Aca…
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Chapters (25)

Introduction to MCP
0:21 Demo: MCP Tool in Cursor
0:40 Demo: MCP Tool in Windsurf
0:54 Demo: MCP Tool in Claude Desktop
1:15 Motivation for MCP
1:38 Building a Tool from Scratch
2:00 Loading LangGraph Docs and Creating a Vector Store
2:44 Testing the Basic Vector Store Query
3:00 Creating a LangChain Tool
3:22 Binding Tools to LLMs
4:00 Bridge to MCP: Connecting Tools to AI Applications
4:24 MCP as a Client-Server Protocol
5:00 How MCP Works with Host Applications
5:37 Server Initialization by Host Applications
6:05 Defining an MCP Server
6:41 Adding Resources to MCP
7:05 Running the MCP Inspector
7:27 Testing Tools in the Inspector
8:06 Configuring MCP Servers for Different Hosts
8:48 Demo: MCP Tool in Cursor (Revisited)
9:10 Demo: MCP Server in Windsurf (Revisited)
9:32 Demo: MCP in Claude Desktop (Revisited)
9:56 Using MCP Resources in Claude Desktop
10:19 Recap: Augmenting LLMs with Context and Tools
10:57 Conclusion and Final Thoughts

Playlist

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30 Shortwave Assistant Deepdive Webinar
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31 Cognitive Architectures for Language Agents
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32 Effectively Building with LLMs in the Browser with Jacob
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33 Data Privacy for LLMs
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34 "Theory of Mind" Webinar with Plastic Labs
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35 LangChain Templates
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36 Using Natural Language to Query Postgres with Jacob
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37 LangServe and LangChain Templates Webinar
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38 Building a Research Assistant from Scratch
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39 Benchmarking RAG over LangChain Docs
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40 Skeleton-of-Thought: Building a New Template from Scratch
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41 Benchmarking Methods for Semi-Structured RAG
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42 LangSmith Highlights: Getting Started
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43 LangSmith Highlights: Debugging
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44 LangSmith Highlights: Datasets
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45 LangSmith Highlights: Evaluation
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46 LangSmith Highlights: Human Annotation
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47 LangSmith Highlights: Monitoring
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