Best of mcp — 2025

  1. 1
    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·44w

    9 MCP Projects for AI Engineers

    A comprehensive collection of 9 Model Control Protocol (MCP) projects designed for AI engineers, covering various applications from local MCP clients and agentic RAG systems to voice agents and synthetic data generators. The projects demonstrate how to integrate MCP with popular tools like Claude Desktop and Cursor IDE, enabling developers to build more sophisticated AI applications with enhanced tool connectivity and context sharing capabilities.

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    Article
    Avatar of communityCommunity Picks·1y

    chatmcp/mcp-directory: directory for Awesome MCP Servers

    A comprehensive guide on setting up a directory for Awesome MCP Servers. The instructions cover cloning the repository, installing dependencies, setting up a database with Supabase, configuring environment variables, and running a development server.

  3. 3
    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·45w

    The Full MCP Blueprint

    MCP (Model Context Protocol) provides a standardized way for LLMs to interact with tools and capabilities, solving the M×N integration problem where every tool needs manual connection to every model. The protocol enables dynamic tool discovery, plug-and-play interoperability between systems like Claude and Cursor, and transforms AI development from prompt engineering to systems engineering. MCP uses a Host-Client-Server architecture with JSON-RPC communication and supports various transport mechanisms including Stdio and HTTP.

  4. 4
    Article
    Avatar of medium_jsMedium·50w

    How I Built a Local MCP Server to Connect Obsidian with AI

    The post details the process of building a custom MCP server to connect personal knowledge bases in Obsidian with AI tools, enabling enhanced, context-aware assistance. It discusses the motivation behind the project, the use of Claude Desktop, and the implementation of the server using Python and FastMCP. The post highlights the ability of AI models to perform tasks like identifying incomplete notes and generating questions from existing content. Emphasizing security and control, it provides insights on integrating local AI resources and suggests future steps for independence from external providers.

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    Article
    Avatar of communityCommunity Picks·42w

    Your Ultimate MCP Server Hub

    MCPHub is a unified management platform that consolidates multiple Model Context Protocol (MCP) servers into a single Server-Sent Events (SSE) endpoint. It provides a dashboard for monitoring server status and simplifies infrastructure management for AI applications. The tool can be quickly deployed using Docker and allows customization through JSON configuration files.

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    Article
    Avatar of communityCommunity Picks·46w

    Arindam200/awesome-ai-apps: Collection of AI Applications

    A curated collection of AI application examples and tutorials featuring popular frameworks like LangChain, LlamaIndex, CrewAI, and Pydantic AI. The repository includes practical implementations of chatbots, AI agents, and LLM-powered applications, along with integration examples for various tools and APIs. It provides setup instructions, video tutorials, and welcomes community contributions for building modern AI applications.

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    Article
    Avatar of collectionsCollections·39w

    Building MCP Servers and Clients From Scratch: A Comprehensive Guide

    Model Context Protocol (MCP) is a communication framework for AI client-server interactions built around four components: tools, resources, prompts, and samplings. The guide covers building MCP servers and clients using TypeScript with Node.js, including integration with GitHub Copilot and debugging with MCP Inspector. It also explores .NET 10's native MCP support for creating AI assistant extensions, featuring weather and random number tools, with streamlined publishing to NuGet for community distribution and dependency management.

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    Article
    Avatar of thomasthorntonThomas Thornton·35w

    Docker MCP Toolkit: Hassle-Free Local Agentic AI with MCP Servers

    Docker MCP Toolkit simplifies running Model Context Protocol servers locally, enabling AI agents to interact with APIs, cloud services, and tools without complex configuration. The toolkit provides a Docker Desktop extension with a searchable catalog of MCP servers for GitHub, Jira, Terraform, and more. It offers secure containerized environments, instant connections to AI tools like GitHub Copilot and Claude, and eliminates manual setup overhead for developers building agentic AI workflows.

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    Article
    Avatar of portkeyportkey·17w

    Understanding MCP Authorization

    MCP (Model Context Protocol) requires authorization controls as it moves from local experimentation to production deployments. The protocol enables AI models to interact with external tools and APIs dynamically, but without authorization, every connected client can access all exposed tools. Authorization in MCP works through server-side enforcement at request time, not connection time, using patterns like token-based authorization, scoped capability access, and role-based policies. Best practices include applying least privilege, using short-lived scoped tokens, authorizing every tool call individually, and making all access auditable. Strong authorization boundaries are essential for safely deploying MCP in shared environments and production systems.

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    Article
    Avatar of dockerDocker·41w

    Top 5 MCP Server Best Practices

    Five essential best practices for building MCP (Model Context Protocol) servers: manage tool budget by avoiding one-tool-per-endpoint patterns, design for AI agents rather than end users with proper error handling, document for both human users and AI agents, test user interactions beyond just functionality using MCP inspector, and package servers as Docker containers for portability. The guide emphasizes that AI agents are the actual consumers of MCP tools, requiring different design considerations than traditional user-facing APIs.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·43w

    10 MCP, RAG and AI Agents Projects

    A curated collection of 10 advanced AI engineering projects covering MCP-powered applications, RAG systems, and AI agents. Projects include video RAG with exact timestamp retrieval, corrective RAG with self-assessment, multi-agent flight booking systems, voice-enabled RAG agents, and local alternatives to ChatGPT's research features. The repository contains 70+ hands-on tutorials focusing on real-world implementations of LLMs, memory-enabled agents, multimodal document processing, and performance optimization techniques like binary quantization for 40x faster RAG systems.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·46w

    Build an MCP Server to Connect to 200+ Data Sources

    A guide to building a Model Context Protocol (MCP) server using MindsDB that can connect to over 200 data sources including Slack, Gmail, GitHub, and Hacker News. The setup uses Docker for local hosting and integrates with Cursor IDE, providing tools to list databases and query federated data through a unified interface. The implementation demonstrates practical use cases like fetching Hacker News data, sending formatted summaries to Slack, and retrieving Gmail messages.

  13. 13
    Article
    Avatar of uxplanetUX Planet·43w

    Figma MCP: Complete Guide

    Figma MCP (Model Context Protocol) enables AI code generators like Cursor to understand Figma designs at a semantic level, providing better design-to-code conversion than screenshot-based approaches. The guide covers setup requirements including Figma Desktop app and compatible code editors, configuration steps for both Figma and Cursor, and troubleshooting common issues like 'get_code' and 'get_image' errors. MCP offers design token awareness and semantic precision, allowing AI to access exact variable names, hierarchy, and constraints for better alignment with design systems.

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    Article
    Avatar of phProduct Hunt·51w

    RapidMCP - Convert your REST API into an MCP Server in minutes!

    RapidMCP allows the conversion of REST API specifications into MCP servers in minutes without any coding. It aims to streamline the process of making APIs MCP-ready, including considerations for OpenAPI Swagger spec and authentication.

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    Article
    Avatar of dockerDocker·34w

    Docker MCP for AI Agents: Real-World Developer Setup

    A comprehensive guide to building AI agents using Docker MCP Toolkit, demonstrating how to create a GitHub repository question-answering agent. The setup uses Docker containers for isolation, MCP Gateway for tool integration, and Docker Compose for orchestration. The approach eliminates environment drift, simplifies scaling, and provides a production-ready development pattern that works consistently from local development to CI/CD pipelines.

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    Video
    Avatar of bytegradByteGrad·46w

    Build Next.js MCP - Your Website & MCP-Server In 1 App!

    A comprehensive tutorial demonstrating how to build a Next.js application that includes both a traditional website and an MCP (Model Context Protocol) server in a single app. The guide covers creating MCP tools that AI agents can invoke, implementing course recommendation functionality based on user experience level, deploying to Vercel with Redis integration, and testing the MCP server with GitHub Copilot. The tutorial also showcases CodeRabbit for automated code reviews and includes practical examples of AI agent interactions with custom MCP endpoints.

  17. 17
    Video
    Avatar of fireshipFireship·1y

    I gave Claude root access to my server... Model Context Protocol explained

    Developers are increasingly adopting the model context protocol (mCP), which is a new standard for building APIs that provides better context for large language models (LLMs). By connecting resources and tools in a server environment, mCP allows these models to perform tasks like writing to databases or managing cloud infrastructure. The post explains how to set up an mCP server, highlights its advantages over traditional API architectures, and discusses the future impact of AI-generated code.

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    Article
    Avatar of vercelVercel·39w

    Grep a million GitHub repositories via MCP

    Grep now supports the Model Context Protocol (MCP), allowing AI agents to search over a million public GitHub repositories through a standardized interface. The MCP server can be easily integrated with AI clients like Cursor and Claude, enabling agents to query code patterns and retrieve relevant snippets in real-time. Vercel built the MCP server quickly using their mcp-handler package, which simplifies the process of exposing existing APIs to AI clients.

  19. 19
    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·45w

    An MCP-powered Voice Agent

    A technical demonstration of building a voice agent using Model Context Protocol (MCP) that can query databases and perform web searches. The system uses AssemblyAI for speech-to-text, Firecrawl for web search, Supabase as the database, LiveKit for orchestration, and Qwen3 as the LLM. The agent transcribes user speech, determines whether to query the database or search the web, and responds via text-to-speech.

  20. 20
    Article
    Avatar of itnextITNEXT·41w

    How to Start Your Own MCP Server with n8n

    n8n version 1.88.0+ includes built-in Model Context Protocol (MCP) support, allowing users to expose workflows as AI-usable tools through MCP Server Trigger nodes and connect to other MCP servers via MCP Client Tool nodes. The guide covers setting up MCP endpoints, configuring authentication, exposing tools, and connecting with AI agents, all without requiring additional installations or Docker images.

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    Article
    Avatar of communityCommunity Picks·50w

    php-mcp/server: Core PHP implementation for the Model Context Protocol (MCP) server

    php-mcp/server is a PHP library designed to simplify the creation of Model Context Protocol (MCP) compliant servers. It facilitates exposing PHP methods as MCP Tools, Resources, or Prompts using PHP 8 Attributes, supporting a specific protocol version and integrating with various MCP clients. The library is PSR-compliant, allowing flexible configurations and integration with different PHP frameworks. Users can set up MCP elements using attribute-based definitions or manual registration, and the package supports multiple transport mechanisms including stdio and HTTP+SSE.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·39w

    MCP Integration with 4 Popular Agentic Frameworks

    Part 8 of an MCP crash course demonstrates how to integrate Model Context Protocol with four popular agentic frameworks: LangGraph, CrewAI, LlamaIndex, and PydanticAI. The tutorial provides step-by-step practical walkthroughs for connecting MCP to each framework, along with detailed implementations. This builds on previous parts covering MCP fundamentals, custom client development, tools/resources/prompts, sampling integration, and security considerations including testing and sandboxing.

  23. 23
    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·33w

    Build a 100% local MCP Server and Client

    Learn to build a completely local Model Context Protocol (MCP) server and client setup for enterprise-grade AI applications. The tutorial covers creating MCP servers using FastMCP, building secure local clients with mcp-use library, and integrating with Stagehand for browser automation. This approach keeps data on your own servers while enabling AI agents to perform tasks like web scraping and form filling through natural language commands.

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    Video
    Avatar of youtubeYouTube·1y

    Learn MCP Servers with Python (EASY)

    This post provides a crash course on mCP servers, explaining their theory, how to create and use them with Python, and integrating AI assistants to check for the latest library documentation. It includes guidance on creating, setting up, and debugging mCP servers using Python, and also covers their use in both cloud desktop and cloud code environments.

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    Article
    Avatar of dailydoseofdsDaily Dose of Data Science | Avi Chawla | Substack·18w

    Finally, MCP Servers Can Deliver UI-rich Experiences!

    MCP servers traditionally only return text/JSON responses without UI capabilities. The open-source mcp-use framework solves this by letting developers create React components that automatically register as MCP tools and render as interactive widgets in ChatGPT. Components placed in a resources/ folder become callable tools with zero boilerplate—no duplicate schemas or manual registration needed. The framework supports the full React ecosystem, hot reloading, and automatic theme syncing with ChatGPT's light/dark mode. A practical example demonstrates building an interactive stock chart widget that displays closing prices over time.

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