Development Tools & DevOps MCP Servers
Streamline your development workflow with our Development Tools & DevOps integrations. Connect with version control systems, CI/CD pipelines, container platforms, and more to build, test, and deploy your AI applications faster and more reliably.
🔧 Build, Test, & Deploy Automation
Development Tools and DevOps MCP Servers
What Are Development Tools & DevOps MCP Servers?
Development Tools and DevOps MCP servers provide AI models with the capability to interact with the software development lifecycle. These servers enable AI to manage source code, execute builds, run tests, and orchestrate deployments, transforming AI into a proactive collaborator in the development process.
Version Control
Manage code repositories, branches, and pull requests on platforms like Git, GitHub, and GitLab.
CI/CD Automation
Automate building, testing, and deploying applications with CI/CD pipeline integrations.
Cloud Management
Provision and manage cloud infrastructure using Infrastructure as Code (IaC) tools.
Terminal & Shell Access
Execute shell commands, manage files, and run scripts in a secure environment.
Monitoring & Debugging
Integrate with error tracking and performance monitoring platforms to ensure application health.
IDE & Editor Integration
Connect with IDEs and code editors to provide development assistance and code analysis.
Available Integrations by Type
Available Development Tools & DevOps MCP Servers
Explore the complete collection of 28 development tools & devops MCP servers with configuration templates and setup guides:
| Server | Description | Setup Guide |
|---|---|---|
| Accessibility Scanner | Accessibility Scanner MCP servers enable AI models to perform WCAG compliance checks, capture annotated screenshots, and generate detailed accessibility reports. | Setup Guide |
| Ansible | Ansible MCP servers enable AI models to interact with Ansible, providing capabilities for infrastructure automation, configuration management, and application deployment. | Setup Guide |
| Auth0 | Auth0 MCP server enables AI models to interact with Auth0 identity and access management platform, providing capabilities for managing applications, users, roles, and authentication flows. | Setup Guide |
| AWS | Interact with Amazon Web Services through your AI assistant - manage EC2, S3, Lambda, and hundreds of AWS services. | Setup Guide |
| Azure DevOps | The Azure DevOps MCP Server enables AI models to interact with Azure DevOps, providing capabilities for managing work items, pull requests, pipelines, and more. | Setup Guide |
| Browserbase | Browserbase MCP server enables AI models to control cloud browsers with Stagehand AI, providing automated page navigation, data extraction, element observation, and web actions. | Setup Guide |
| Browserless | Browserless MCP server provides AI-controlled cloud and self-hosted headless browsers with smart scraping, crawling, PDF generation, and anti-bot protection for Puppeteer and Playwright. | Setup Guide |
| Cloudflare | Interact with Cloudflare services using natural language through the Model Context Protocol. | Setup Guide |
| ConsoleSpy | ConsoleSpy MCP servers enable AI models to interact with browser console logs, providing capabilities for real-time debugging, error monitoring, and application analysis. | Setup Guide |
| Context7 | Context7 MCP server provides up-to-date, version-specific code documentation directly in LLM context, preventing hallucinated APIs and outdated code generation. | Setup Guide |
| Datadog | Datadog MCP servers enable AI models to interact with Datadog observability: metrics, logs, traces, monitors, dashboards, incidents, and infrastructure insights. | Setup Guide |
| Docker | Manage Docker containers, images, networks, and volumes through AI assistants using natural language with the Docker MCP Server. | Setup Guide |
| Figma: Automate Design-to-Code Workflows | Connect Figma designs to VS Code and Cursor. | Setup Guide |
| Flutter | Flutter MCP servers enable AI models to interact with Flutter projects, providing capabilities for code analysis, formatting, testing, and documentation retrieval. | Setup Guide |
| GCP | Manage Google Cloud Platform resources through your AI assistant - Compute Engine, Cloud Run, GKE, and more. | Setup Guide |
| Git | Git MCP servers enable AI models to interact with Git version control systems, providing capabilities for repository management, branch operations, commit handling, and collaborative development workflows. | Setup Guide |
| GitHub Actions | Manage CI/CD workflows with GitHub Actions through your AI assistant - trigger runs, check status, and debug failures. | Setup Guide |
| GitHub | GitHub's official MCP server enables AI assistants to manage repositories, issues, pull requests, Actions workflows, and code security directly through natural language. | Setup Guide |
| Jenkins | Integrate with Jenkins CI/CD pipelines through your AI assistant - trigger builds, check status, and manage jobs. | Setup Guide |
| Kubernetes | Connect your AI assistant to Kubernetes clusters for cluster management, pod inspection, deployment automation, and troubleshooting. | Setup Guide |
| Playwright | Playwright MCP servers enable AI models to perform cross-browser automation, modern web testing, accessibility testing, and end-to-end testing workflows using Playwright's powerful browser automation capabilities. | Setup Guide |
| Puppeteer | Puppeteer MCP servers enable AI models to perform browser automation, web scraping, testing workflows, and screenshot generation through headless Chrome/Chromium control. | Setup Guide |
| Sentry | Sentry MCP servers enable AI models to interact with Sentry's error monitoring and performance tracking platform, providing capabilities for analyzing errors, tracking performance, and assisting in debugging applications. | Setup Guide |
| OpenAPI/Swagger | Swagger MCP servers enable AI models to interact with APIs defined by Swagger specifications, providing capabilities for automatic tool generation, API key handling, and dynamic interaction with various APIs. | Setup Guide |
| Terminal | Terminal MCP servers enable AI models to interact with command-line interfaces and shells, providing capabilities for executing commands, managing processes, file operations, and handling terminal I/O in a secure environment. | Setup Guide |
| Terraform | Manage infrastructure as code with Terraform through your AI assistant - plan, apply, and inspect infrastructure resources. | Setup Guide |
| Vercel | Integrate Vercel with your AI assistants using the Model Context Protocol (MCP) for seamless deployment management, project control, and environment configuration. | Setup Guide |
| Zig | Zig MCP servers enable AI models to interact with Zig projects, providing capabilities for build system management, code optimization, and code generation. | Setup Guide |
Related Articles & Guides
Browserless MCP Server
Browserless MCP server provides AI-controlled cloud and self-hosted headless browsers with smart scraping, crawling, PDF generation, and anti-bot protection for Puppeteer and Playwright.
Browserbase MCP Server
Browserbase MCP server enables AI models to control cloud browsers with Stagehand AI, providing automated page navigation, data extraction, element observation, and web actions.
Docker MCP Server
Manage Docker containers, images, networks, and volumes through AI assistants using natural language with the Docker MCP Server.