Discover Awesome MCP Servers

Okta MCP Server

Mengaktifkan Claude untuk berinteraksi dengan sistem manajemen pengguna Okta, menyediakan kemampuan untuk mengambil detail pengguna, membuat daftar pengguna dengan opsi penyaringan, dan mengelola grup pengguna.

Trello-Claude интеграция

Интеграция Claude с Trello через MCP Server на Smithery.ai

MemGPT MCP Server

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Flipt MCP Server

Server MCP Flipt memungkinkan asisten AI dan LLM untuk berinteraksi langsung dengan *feature flag*, segmen, dan evaluasi Anda melalui antarmuka yang terstandardisasi. Contohnya, Anda dapat bertanya kepada asisten AI Anda: "Bagaimana status *flag* 'dark-mode' saat ini?"

MCP-Wikipedia-API-Server

Server FastAPI-MCP yang mengambil ringkasan Wikipedia untuk asisten AI, di-deploy menggunakan Google Colab dan Ngrok.

ConnectWise Manage MCP Server

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MCP-SSE4

created from MCP server demo

mcp-use-didwba

An example of an MCP client and server using didwba as the authentication technology.

Unity AI MCP Server

An MCP server that provides AI-powered tools and assistance for Unity game development

Model Context Protocol Server for NebulaGraph

Mirror of

Perplexity MCP Server

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Generate images MCP server

A Model Context Protocol server for generating images

Crawl4AI MCP Server

Crawl4AI-MCP: Server perayapan web dan analisis konten yang kuat, menggabungkan *web scraping* yang ditargetkan dengan pemrosesan Claude AI. Ekstrak wawasan dari situs web tertentu dengan kedalaman yang dapat disesuaikan, pemilihan konten, dan kemampuan analisis AI.

temp

MCP server for youtube! Allows you to directly search and access transcripts on youtube through a single call in the Claude LLM

Zipic MCP Server

A Model Context Protocol server that provides image compression and optimization capabilities through Zipic app.

gitlab-mr-mcp-server

Here are a few ways an MCP (presumably referring to a **Merge Confidence Pipeline** or similar) server could work with GitLab Merge Requests (MRs), along with explanations: **1. Automated Code Quality Checks & Reporting:** * **How it works:** The MCP server listens for GitLab MR events (e.g., MR created, MR updated, commit pushed). When an event occurs, the MCP server pulls the code from the MR branch. It then runs a suite of code quality checks (linting, static analysis, security scans, unit tests, integration tests, etc.). The results are then reported back to the GitLab MR. * **GitLab Integration:** * **GitLab API:** The MCP server uses the GitLab API to: * Fetch the code from the MR. * Post comments directly on the MR with the results of the checks. This is crucial for providing immediate feedback to the developer. * Update the MR status (e.g., "pending," "success," "failure") based on the outcome of the checks. This allows GitLab to block merging if the checks fail. * Potentially create GitLab issues automatically if certain types of problems are detected. * **Webhooks:** GitLab sends webhooks to the MCP server to notify it of MR events. This is the trigger for the MCP server to start its analysis. * **Benefits:** * Early detection of code quality issues. * Automated feedback loop for developers. * Enforcement of coding standards. * Reduced risk of introducing bugs into the main codebase. * **Example:** Imagine an MCP server running SonarQube. When a developer creates an MR, the MCP server runs SonarQube analysis. SonarQube finds a code smell and a potential security vulnerability. The MCP server posts comments on the MR highlighting these issues and sets the MR status to "failed." The developer must fix the issues before the MR can be merged. **2. Automated Performance Testing:** * **How it works:** Similar to code quality checks, but focuses on performance. The MCP server deploys the code from the MR branch to a test environment. It then runs performance tests (e.g., load testing, stress testing, benchmark testing). The results are compared against a baseline. * **GitLab Integration:** * **GitLab API:** Used to fetch code, post comments with performance metrics (e.g., response times, throughput), and update MR status. * **Webhooks:** Triggered by MR events. * **Benefits:** * Identifies performance regressions early in the development cycle. * Ensures that new code doesn't negatively impact application performance. * Provides data-driven insights for performance optimization. **3. Automated Security Vulnerability Scanning:** * **How it works:** The MCP server uses static analysis tools, dynamic analysis tools (DAST), and software composition analysis (SCA) to identify security vulnerabilities in the code and its dependencies. * **GitLab Integration:** * **GitLab API:** Used to fetch code, post comments with vulnerability reports, and update MR status. GitLab's own security scanning features can also be integrated and enhanced by an external MCP server. * **Webhooks:** Triggered by MR events. * **Benefits:** * Proactive identification of security vulnerabilities. * Reduced risk of security breaches. * Compliance with security standards. **4. Custom Merge Checks & Policies:** * **How it works:** The MCP server enforces custom merge policies that go beyond the standard GitLab merge checks. For example, it might require a certain number of approvals from specific teams, or it might require that certain types of tests pass before a merge is allowed. * **GitLab Integration:** * **GitLab API:** Used to fetch MR data (e.g., approvals, comments, test results), enforce policies, and update MR status. * **Webhooks:** Triggered by MR events. * **Benefits:** * Enforcement of complex merge policies. * Improved code quality and security. * Reduced risk of accidental merges. **Key Technologies & Considerations:** * **GitLab API:** Understanding the GitLab API is essential for building an MCP server that integrates with GitLab. Pay close attention to the MR API endpoints. * **Webhooks:** Configure GitLab to send webhooks to your MCP server for relevant MR events. * **CI/CD Pipelines:** The MCP server can often be integrated into GitLab CI/CD pipelines. This allows you to run the MCP checks as part of your automated build and test process. * **Authentication:** The MCP server needs to authenticate with the GitLab API. Use a secure authentication method, such as OAuth 2.0 or a personal access token. * **Scalability:** The MCP server needs to be able to handle a large number of MRs concurrently. Consider using a scalable architecture, such as a microservices architecture. * **Configuration:** Make the MCP server configurable so that you can easily customize the checks and policies that it enforces. * **Reporting:** Provide clear and concise reports of the MCP server's findings. Make it easy for developers to understand the issues and how to fix them. **Indonesian Translation of Key Concepts:** * **Merge Request (MR):** Permintaan Penggabungan (PP) * **Code Quality:** Kualitas Kode * **Security Vulnerability:** Kerentanan Keamanan * **Performance Testing:** Pengujian Kinerja * **Static Analysis:** Analisis Statis * **Dynamic Analysis:** Analisis Dinamis * **Software Composition Analysis (SCA):** Analisis Komposisi Perangkat Lunak * **Webhook:** Kait Web * **GitLab API:** API GitLab * **Merge Confidence Pipeline (MCP):** Alur Keyakinan Penggabungan (AKP) (This is a direct translation, but the acronym might not be commonly used in Indonesian. You might need to explain the concept more fully.) * **Automated:** Otomatis * **Baseline:** Garis Dasar * **Regression:** Regresi * **Throughput:** Hasil Kerja * **Response Time:** Waktu Respon * **Load Testing:** Pengujian Beban * **Stress Testing:** Pengujian Tekanan * **Benchmark Testing:** Pengujian Tolok Ukur * **Code Smell:** Bau Kode (This is a direct translation, but the concept is understood in Indonesian development circles.) * **Microservices Architecture:** Arsitektur Layanan Mikro **Example Indonesian Explanation:** "Server AKP (Alur Keyakinan Penggabungan) dapat bekerja dengan Permintaan Penggabungan (PP) GitLab dengan cara melakukan pemeriksaan kualitas kode secara otomatis. Ketika seorang pengembang membuat PP, server AKP akan mengambil kode dari cabang PP tersebut. Kemudian, server AKP akan menjalankan serangkaian pengujian, seperti analisis statis dan pengujian unit. Hasil pengujian ini akan dilaporkan kembali ke PP GitLab, memberikan umpan balik langsung kepada pengembang. Jika ada masalah, server AKP dapat menambahkan komentar pada PP dan mengubah status PP menjadi 'gagal', mencegah PP tersebut digabungkan sampai masalah diperbaiki." (Translation: "An MCP (Merge Confidence Pipeline) server can work with GitLab Merge Requests (MRs) by performing automated code quality checks. When a developer creates an MR, the MCP server will fetch the code from the MR branch. Then, the MCP server will run a series of tests, such as static analysis and unit tests. The results of these tests will be reported back to the GitLab MR, providing direct feedback to the developer. If there are problems, the MCP server can add comments to the MR and change the MR status to 'failed', preventing the MR from being merged until the problems are fixed.") In summary, an MCP server enhances the GitLab MR process by automating checks, enforcing policies, and providing valuable feedback to developers, ultimately leading to higher quality and more secure code. The key is to leverage the GitLab API and webhooks to create a seamless integration. Remember to choose the right tools and technologies based on your specific needs and requirements.

EntityIdentification

Server MCP (Model Context Protocol) untuk mengidentifikasi apakah dua set data berasal dari entitas yang sama.

Awesome MCP Servers

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MCP-Servers

This repo uses CAMEL AI to create mcp servers for various use cases

Directus MCP Server

An MCP server to simplify Directus collection management

Project Opener MCP Server

MCP server for easily opening code3 projects in either VS Code or Visual Studio

Time Mcp

Memberikan Kemampuan Kesadaran Waktu pada LLM. Berdayakan LLM Anda dengan kemampuan kesadaran waktu. Akses waktu saat ini, konversi antar zona waktu, dan dapatkan stempel waktu dengan mudah. Tingkatkan aplikasi Anda dengan fungsionalitas terkait waktu yang presisi.

OpenAI MCP - DALL-E API Integration for Roo Code

Sebuah server Protokol Konteks Model yang memungkinkan asisten AI untuk menghasilkan gambar melalui API DALL-E OpenAI dengan dukungan penuh untuk semua opsi yang tersedia dan kontrol yang terperinci.

Odoo MCP Server

Implementasi server MCP yang terintegrasi dengan sistem ERP Odoo, memungkinkan asisten AI untuk berinteraksi dengan data dan fungsionalitas Odoo melalui Protokol Konteks Model.