Discover Awesome MCP Servers

Linkup Model Context Protocol

Versi Javascript dari server Linkup MCP.

Backlog MCP Server

Sebuah server Protokol Konteks Model yang memungkinkan Claude berinteraksi dengan alat manajemen proyek Backlog melalui integrasi API, memungkinkan pengelolaan proyek, isu, halaman wiki, dan sumber daya Backlog lainnya.

Remote MCP Server (Authless)

Enables deployment of MCP servers on Cloudflare Workers without authentication requirements. Provides a template for creating custom tools that can be accessed remotely via Claude Desktop or the Cloudflare AI Playground.

Enact Protocol MCP

Server MCP untuk protokol enact

DIE MCP Server

An MCP server that enables AI agents to analyze executable files using Detect It Easy (DIE), providing capabilities to examine file structures, detect packers, compilers, and gather other forensic information.

mcp-starter

mcp-starter is a secure, starter framework for building MCP servers with JWT-based authentication, multi-tenant enforcement, and schema validation. Built with Node.js and Docker

MCP SQL Server

A Model Context Protocol server that provides AI assistants with comprehensive access to SQL databases, enabling schema inspection, query execution, and database operations with enterprise-grade security.

ZeroEntropy Zerank MCP Server

Provides document reranking capabilities via the ZeroEntropy Zerank API, allowing AI assistants to sort documents by relevance to a user query through the Model Context Protocol.

agent-rules-mcp

MCP server that enables your agents to use coding rules from any or your GitHub repository. Instead of workspace rules files, you can now prompt agents to access the your coding rules from any repository.

Solid Multi-Tenant DevOps MCP Server

Enables AI-first DevOps management of multi-tenant Solid SaaS platforms through natural language conversation. Monitor thousands of tenant instances, track AI agent performance, handle errors, manage billing, and provision new tenants directly through Claude Desktop.

MCPAuth

A self-hostable OAuth 2.0 server designed for the Model-Context-Protocol (MCP) that enables you to secure your MCP applications with a robust implementation you control.

Web3 Research MCP

Penelitian Mendalam untuk kripto - gratis & sepenuhnya lokal

Config MCP Server

Enables AI assistants to search documentation, read and update configuration files, and discover settings across your development workspace. Supports JSON, YAML, TOML, and Markdown files with seamless integration for GitHub Copilot and other MCP clients.

Codebase MCP Server

A Model Context Protocol server that analyzes application codebases with real-time file watching, providing AI assistants like Claude with deep insights into project structure, code patterns, and architecture.

MS SQL MCP Server

A bridge that allows AI assistants like Claude to directly query and explore Microsoft SQL Server databases without requiring coding experience.

SMU Schedule MCP Server

Enables management of Sangmyung University academic information including schedules, meals, notices, and exam details. Provides tools to query, search, add, and delete university data through a MySQL database connection.

stock-analytics-mcp-server

Sebuah server untuk analisis saham menggunakan MCP dan Yahoo Finance API.

Guía de Instalación de Supabase MCP Server

Tentu, berikut adalah terjemahan dari "Guía detallada de instalación para Supabase MCP Server" ke dalam bahasa Indonesia: **Panduan Instalasi Lengkap untuk Supabase MCP Server** Atau, bisa juga: **Panduan Instalasi Mendetail untuk Server Supabase MCP** Kedua terjemahan tersebut menyampaikan arti yang sama. Pilihan mana yang lebih baik tergantung pada preferensi gaya Anda.

Google Contacts MCP Server

Enables AI assistants to access and search Google Contacts through per-user OAuth authentication on serverless AWS Lambda. Provides read-only access to personal contacts with zero data storage and real-time API queries.

OCI MCP Server

Enables interaction with Oracle Cloud Infrastructure services through a unified interface. Supports comprehensive OCI resource management including compute instances, storage, networking, databases, and monitoring through natural language commands in VS Code.

Codebase RAG MCP Server

Enables semantic search and retrieval of code files using embeddings stored in PostgreSQL. Supports intelligent codebase exploration through natural language queries, file listing, and content retrieval.

MCP-Todoist Integration

Here are a few options for an MCP (presumably referring to a **Minimal, Complete, and Verifiable Prototype**) server for Todoist integration for natural language task management, along with considerations for each: **Option 1: Simple Flask/FastAPI Server with Todoist API** * **Description:** A lightweight Python server using Flask or FastAPI. It receives natural language input, uses a basic NLP library (like spaCy or NLTK) to extract keywords, and then uses the Todoist API to create tasks. * **Pros:** * **Simple to implement:** Flask/FastAPI are easy to learn and use. * **Direct Todoist integration:** Uses the official Todoist API. * **Good for a basic prototype:** Focuses on core functionality. * **Cons:** * **Limited NLP capabilities:** Basic keyword extraction won't handle complex sentences or context well. * **Requires API key management:** You'll need to handle Todoist API keys securely. * **Scalability:** Not designed for high traffic. * **Example Workflow:** 1. User sends: "Remind me to buy milk tomorrow at 6 PM" 2. Server: * Receives the text. * Uses spaCy to identify "buy milk" as the task, "tomorrow" as the date, and "6 PM" as the time. * Uses the Todoist API to create a task with the content "buy milk" and a due date/time of tomorrow at 6 PM. * **Tech Stack:** * Python * Flask or FastAPI * spaCy or NLTK (for NLP) * `todoist-api-python` (Python Todoist API library) * **MCP Focus:** Demonstrates the basic flow of receiving text, extracting information, and creating a Todoist task. **Option 2: Serverless Function (AWS Lambda, Google Cloud Functions, Azure Functions) with Todoist API** * **Description:** A serverless function that triggers on an HTTP request. It performs the same NLP and Todoist API integration as Option 1, but without managing a server. * **Pros:** * **Scalable:** Serverless functions scale automatically. * **Cost-effective:** You only pay for the function when it's used. * **Easy deployment:** Relatively easy to deploy. * **Cons:** * **Cold starts:** Serverless functions can have a delay when they're first invoked. * **Limited execution time:** Serverless functions have time limits. * **Debugging:** Debugging can be more challenging than with a traditional server. * **Example Workflow:** Same as Option 1. * **Tech Stack:** * Python (or Node.js, Go, etc.) * AWS Lambda, Google Cloud Functions, or Azure Functions * spaCy or NLTK (for NLP) * `todoist-api-python` (or equivalent for other languages) * **MCP Focus:** Demonstrates a scalable and cost-effective way to integrate with Todoist. **Option 3: Using a Pre-built NLP Service (Dialogflow, LUIS, Rasa) with a Webhook to Todoist** * **Description:** Leverages a pre-built NLP service to handle the natural language understanding. The NLP service is configured to recognize task-related intents and entities (e.g., task description, due date, priority). When an intent is matched, the NLP service sends a webhook to your server (or serverless function), which then uses the Todoist API to create the task. * **Pros:** * **Improved NLP:** Pre-built NLP services offer more sophisticated natural language understanding. * **Easier intent and entity management:** These services provide tools for defining and managing intents and entities. * **Reduced coding effort:** You don't need to write as much NLP code. * **Cons:** * **Dependency on a third-party service:** You're reliant on the NLP service's availability and pricing. * **Learning curve:** You need to learn how to use the NLP service. * **Cost:** Some NLP services can be expensive for high usage. * **Example Workflow:** 1. User sends: "Remind me to buy milk tomorrow at 6 PM" 2. Dialogflow (or LUIS, Rasa): * Recognizes the intent "create_task". * Extracts the entities: `task_description` = "buy milk", `due_date` = "tomorrow", `due_time` = "6 PM". * Sends a webhook to your server with the intent and entities. 3. Server: * Receives the webhook. * Uses the Todoist API to create a task with the extracted information. * **Tech Stack:** * Python (or Node.js, Go, etc.) * Flask or FastAPI (for the webhook endpoint) * Dialogflow, LUIS, or Rasa (for NLP) * `todoist-api-python` (or equivalent for other languages) * **MCP Focus:** Demonstrates the use of a pre-built NLP service for more accurate and robust natural language understanding. **Recommendation for an MCP:** Start with **Option 1 (Simple Flask/FastAPI Server)**. It's the easiest to implement and will allow you to quickly demonstrate the core functionality of integrating natural language input with Todoist. Once you have a working prototype, you can then explore Option 3 (using a pre-built NLP service) to improve the accuracy and robustness of your NLP. Option 2 (Serverless) is a good choice for deployment once you have a working prototype. **Indonesian Translation of the Recommendation:** **Rekomendasi untuk MCP (Minimal, Complete, and Verifiable Prototype):** Mulailah dengan **Opsi 1 (Server Flask/FastAPI Sederhana)**. Ini adalah yang paling mudah diimplementasikan dan akan memungkinkan Anda untuk dengan cepat mendemonstrasikan fungsionalitas inti dari mengintegrasikan input bahasa alami dengan Todoist. Setelah Anda memiliki prototipe yang berfungsi, Anda kemudian dapat menjelajahi Opsi 3 (menggunakan layanan NLP yang sudah jadi) untuk meningkatkan akurasi dan ketahanan NLP Anda. Opsi 2 (Serverless) adalah pilihan yang baik untuk penyebaran setelah Anda memiliki prototipe yang berfungsi.

MCP Server Cookiecutter Template

Cara Mudah dan Terkelola untuk Membuat Server MCP Anda Sendiri

Filesystem MCP Server

A Model Context Protocol server that provides AI agents with secure access to local filesystem operations, enabling reading, writing, and managing files through a standardized interface.

Template MCP

A secure MCP server using FastMCP and Eunomia Authorization, providing granular access control with dynamic JSON policies.

INDIAN MEDICINES (MCP SERVER)

Server API komprehensif untuk pencarian informasi obat, saran alternatif, dan analisis komposisi. Server ini menyediakan berbagai endpoint untuk mencari, memfilter, dan menganalisis data obat dengan fitur-fitur canggih seperti pencocokan fuzzy dan perbandingan harga.

Lizeur

Enables AI assistants to extract and read content from PDF documents using Mistral AI's OCR capabilities. Provides intelligent caching and returns clean markdown text for easy integration with AI workflows.