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# CUSTOM MCP SERVER > Get started building your own server to use in Claude for Desktop and other clients. This README file provides a comprehensive guide on creating a custom MCP server and publishing it as a package to PyPI. Follow the steps outlined to build, configure, and deploy your server effectively. --- ## What is Model Context Protocol (MCP)? **MCP** stands for **Model Context Protocol** — it's a protocol that allows developers to extend AI assistants (like Claude) with custom tools and servers. - **Example**: You can build weather servers, calculators, finance assistants, or anything you imagine. MCP is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications. Just as USB-C provides a standardized way to connect your devices to various peripherals and accessories, MCP provides a standardized way to connect AI models to different data sources and tools. --- ## General Architecture ```mermaid flowchart LR subgraph "Your Computer" Host["Host with MCP Client\n(Claude, IDEs, Tools)"] S1["MCP Server A"] S2["MCP Server B"] S3["MCP Server C"] Host <-->|"MCP Protocol"| S1 Host <-->|"MCP Protocol"| S2 Host <-->|"MCP Protocol"| S3 S1 <--> D1[("Local\nData Source A")] S2 <--> D2[("Local\nData Source B")] end subgraph "Internet" S3 <-->|"Web APIs"| D3[("Remote\nService C")] end ``` ### Key Components - **MCP Hosts**: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP. - **MCP Clients**: Protocol clients that maintain 1:1 connections with servers. - **MCP Servers**: Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol. - **Local Data Sources**: Your computer's files, databases, and services that MCP servers can securely access. - **Remote Services**: External systems available over the internet (e.g., thro…
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