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    An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.
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    MIT
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    Enables interaction with Azure DevOps services through Personal Access Token authentication. Provides 75 tools for managing work items, builds, repositories, pull requests, and other DevOps operations via both CLI and HTTP API interfaces.
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    MIT
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    Enables MCP clients to inspect and manage Semaphore UI automation through its management API, covering projects, templates, tasks, logs, inventories, repositories, and related configuration. It works over stdio or Streamable HTTP with schema-validated tools, read-only mode, project allowlists, and a bounded task-wait helper.
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    MIT
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    Enables AI agents and external systems to programmatically trigger and monitor Jenkins jobs, retrieve build status and logs via MCP standards.
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    An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.
    2
    MIT
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    Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.
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    24 PyPI
    MIT
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    Enables AI assistants to set up, run, and manage Ballerina + Salesforce integrations inside a WSO2 Integrator workspace, providing 18 tools for OAuth2 token acquisition, project scaffolding, building, deploying, and stopping the integration service.
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    Enables AI assistants to create and validate workflow diagrams using FlowZap's text-based DSL. Generates shareable playground URLs for visualizing flowcharts, process diagrams, and CI/CD pipelines through natural language descriptions.
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    441 npm
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    MIT
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    Enables AI assistants to deploy, manage, and rollback websites via the Krexel API, supporting site uploads, deploys, logs, rollbacks, environment variables, and status checks.
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    72 npm
    MIT
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    Enables building MSBuild projects and solutions by dynamically locating MSBuild and providing customizable build options, with clear error reporting and cross-client compatibility.
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    MIT
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    Share Android and iOS builds with testers from your AI agent. Sets up the build for Expo, React Native, Flutter or native apps, uploads the .apk or .ipa, and returns an install link and QR code, plus tester feedback.
    12
    77 npm
    MIT
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    A secure MCP server providing read-only access to Argo CD instances using browser session cookies, enabling querying of applications, projects, clusters, and repositories.
    14
    MIT
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    An MCP server that unpacks and structures Playwright trace.zip archives so AI agents can perform root-cause analysis on CI failures, with 16 focused tools for inspection, DOM/UI analysis, root-cause analysis, and performance analysis.
    19
    80 npm
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    MIT
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    Enables AI agents to scan code for security vulnerabilities using multiple static analysis tools, with support for filtering, deduplication, and CI/CD integration.
    27
    60 PyPI
    4
    MIT
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    Provides structured access to Xcode development tools including xcrun, xcodebuild, and xctrace for building, testing, and analyzing projects.
    15
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    MIT
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    MCP server for Jenkins (with optional GitLab integration) that lets AI assistants list jobs, trigger and track deployments, fetch build logs, and verify whether tickets are deployed, without touching the Jenkins UI.
    17
    MIT
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    An MCP server that enables AI assistants to manage database migrations and validate schemas using the Ariga Atlas CLI. It provides tools for applying migrations, generating diffs, linting, and checking migration status through natural language.
    6
    7 npm
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    MIT
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    A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.
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    Enables AI agents to manage Databricks Lakeflow jobs by building and uploading Python wheels and triggering runs with specific arguments. It provides a structured way to orchestrate complex data experiments and monitor execution directly on Databricks clusters.
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