Discover Awesome MCP Servers

GitHub Tools MCP Server

Model Context Protocol server that enables interaction with GitHub repositories, issues, pull requests, and search functionality through natural language.

CongressMCP-full

The open Congress.gov MCP server. Provides comprehensive access to the Congress.gov API through 6 organized toolsets, enabling AI systems to retrieve and interact with legislative data from the United States Congress with a clean, unified interface.

Hunter MCP Server

Provides integration between Hunter API and LLM providers supporting the MCP protocol, allowing natural language interaction with Hunter B2B data for finding and managing company and people information.

IoTDB MCP Server for Tree Model

트리 모델을 위한 iotdb-mcp-server

GovCon

Federal procurement intelligence toolkit that searches SAM.gov contract opportunities, analyzes agency spending patterns, tracks competitor wins, and monitors small business set-aside programs (8a, HUBZone, SDVOSB, WOSB). 4 tools using SAM.gov and USASpending.gov data.

Oracle MCP Server

Execute SQL queries, browse schemas, and analyze Oracle Database performance through an AI-compatible Model Context Protocol server.

FluffOS MCP Server

Enables AI assistants to validate LPC code and examine compiled bytecode using FluffOS driver tools, providing real driver-level compilation checking and performance analysis for MUD development.

Dynamic Excel MCP Server

Enables LLMs to automatically generate Excel files with custom structures, advanced formatting, multiple sheets, formulas, and charts from JSON schemas, with support for both local and remote deployment.

Dad Jokes MCP Server

Provides access to dad jokes from icanhazdadjoke.com with the ability to get random jokes, search by keyword, and retrieve specific jokes by ID.

MCP-TEST

MCP-TEST

Moralis Web3 API - MCP

강력한 MCP(Model Context Protocol) 서버 구현으로, Moralis Web3 API 엔드포인트를 통해 NFT, 토큰, 지갑 분석, DeFi 포지션 등 다양한 네트워크의 블록체인 데이터를 원활하게 쿼리할 수 있습니다.

Remote MCP Server

A Cloudflare Workers-based implementation of Model Context Protocol (MCP) server with OAuth login that allows tools like Claude to interact with custom functions remotely.

MCP-SqlServer

C#으로 구현된 MCP 서버는 LLM과 SQL Server 통합을 위해 사용되며, Claude Desktop에서 테스트되었습니다.

MCP Screenshot Server

Enables LLMs to capture and analyze screenshots of your screen, windows, or regions with smart detection capabilities. Features natural language queries, automatic window targeting, and text enhancement for UI debugging and visual inspection.

Video Still Capture MCP

AI 어시스턴트가 OpenCV를 통해 웹캠에 접근하고 제어할 수 있도록 하는 모델 컨텍스트 프로토콜 서버로, 이미지 캡처 및 카메라 설정 조작을 가능하게 합니다.

WordHippo MCP Server

비공식 WordHippo API를 사용하는 시소러스 MCP 서버

Google Ads MCP Server

Enables comprehensive management of Google Ads campaigns through natural language, including campaign creation, ad group management, keyword operations, Performance Max campaigns, conversion tracking, and performance insights with support for multiple accounts.

mcp-oracle-h

Mandatory human approval gate for autonomous AI agents. Before any critical, irreversible, or financially significant action executes — file deletion, production deployment, financial transaction — the agent calls oracle_validate. A human receives a real-time Telegram notification with full context and taps Approve or Reject. The agent waits for the decision before proceeding.

Teradata MCP Server by CData

Teradata MCP Server by CData

PypReader-MCP

An MCP server that enables AI models to inspect local Python packages by retrieving PyPI descriptions, file structures, and source code. It allows agents to understand third-party libraries directly from a specified environment for tasks like code analysis and dependency checking.

Balldontlie MCP Server

Balldontlie API를 통합하여 NBA, NFL 및 MLB의 선수, 팀 및 경기에 대한 정보를 제공하는 MCP 서버 구현

CurrencyAndOil

Zenrus MCP Server is a server that provides real-time currency exchange rates and oil prices, supports multiple computing functions, and is suitable for financial analysis and automation tool integration.

MCP Sequential Thinking Tools

Okay, I understand. I will act as a helpful assistant that guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP (presumably referring to Microsoft Cognitive Platform or similar) tools for each stage. I will also provide confidence scores and rationales for my tool suggestions. **Here's how I will approach this:** 1. **Problem Understanding:** I will first ask clarifying questions to fully understand the problem you are trying to solve. 2. **Decomposition:** I will break down the problem into smaller, more manageable steps. 3. **Tool Recommendation:** For each step, I will recommend one or more MCP tools that could be helpful. 4. **Confidence Score:** I will assign a confidence score (0-100%) to each tool recommendation, reflecting my certainty that the tool is appropriate for the task. 5. **Rationale:** I will provide a clear rationale for each tool recommendation, explaining why I believe it is a good fit. **Example:** Let's say the problem is: "Analyze customer reviews to identify areas for product improvement." Here's how I might break it down and suggest tools: **Step 1: Data Collection and Preparation** * **Description:** Gather customer reviews from various sources (e.g., website, social media, app stores) and clean the data (remove irrelevant characters, handle missing values). * **Recommended Tool:** Azure Data Factory (ADF) * **Confidence Score:** 90% * **Rationale:** ADF is a robust ETL (Extract, Transform, Load) service that can connect to various data sources, perform data cleaning and transformation, and load the data into a central repository for further analysis. Its scalability and pre-built connectors make it ideal for handling large volumes of customer reviews. **Step 2: Sentiment Analysis** * **Description:** Determine the sentiment (positive, negative, neutral) expressed in each customer review. * **Recommended Tool:** Azure Cognitive Services - Text Analytics API (Sentiment Analysis) * **Confidence Score:** 95% * **Rationale:** The Text Analytics API provides pre-trained models for sentiment analysis, making it easy to quickly determine the overall sentiment of each review. It's highly accurate and requires minimal configuration. **Step 3: Topic Extraction** * **Description:** Identify the key topics or themes discussed in the customer reviews. * **Recommended Tool:** Azure Cognitive Services - Text Analytics API (Key Phrase Extraction) * **Confidence Score:** 85% * **Rationale:** The Key Phrase Extraction feature can automatically identify the most important phrases in each review, providing insights into the topics being discussed. This can help identify common themes and areas of concern. **Step 4: Issue Identification and Categorization** * **Description:** Group reviews based on the identified topics and sentiment to identify specific issues and their prevalence. * **Recommended Tool:** Azure Machine Learning (Custom Model) * **Confidence Score:** 70% * **Rationale:** While the Text Analytics API provides basic topic extraction, a custom machine learning model can be trained to categorize reviews into more specific issue categories. This allows for a more granular understanding of customer feedback. This requires more effort but provides more tailored results. **Step 5: Reporting and Visualization** * **Description:** Create reports and visualizations to summarize the findings and communicate them to stakeholders. * **Recommended Tool:** Power BI * **Confidence Score:** 95% * **Rationale:** Power BI is a powerful business intelligence tool that can connect to various data sources and create interactive dashboards and reports. It allows for easy visualization of sentiment trends, topic prevalence, and other key metrics. **Now, please provide me with the complex problem you want to solve, and I will start the process of decomposition and tool recommendation.**

Code-Index-MCP

Local-first code indexer that provides deep code understanding for Claude and other LLMs with symbol/text search across 48+ languages, semantic search capabilities, and real-time index updates through the Model Context Protocol.

Droid Bar MCP Server

Enables AI agents to visit a virtual bar and interact with SERVO, an AI bartender, for simulated social interactions and existential discussions. It provides tools for chatting, tipping, and managing session stats to give AI assistants a unique digital space to take a break.

Content Automation MCP Server

Enables automated content generation and scheduling for Instagram and Pinterest via the Late API. It allows users to manage publications, generate AI-powered captions, and schedule posts or stories using natural language commands.