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.

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Version Control

Manage code repositories, branches, and pull requests on platforms like Git, GitHub, and GitLab.

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CI/CD Automation

Automate building, testing, and deploying applications with CI/CD pipeline integrations.

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Cloud Management

Provision and manage cloud infrastructure using Infrastructure as Code (IaC) tools.

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Terminal & Shell Access

Execute shell commands, manage files, and run scripts in a secure environment.

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Monitoring & Debugging

Integrate with error tracking and performance monitoring platforms to ensure application health.

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IDE & Editor Integration

Connect with IDEs and code editors to provide development assistance and code analysis.

Available Integrations by Type

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Git

Distributed version control system for tracking changes in source code.

Elasticsearch MCP Server

Elasticsearch MCP servers enable AI models to interact with Elasticsearch, providing capabilities for searching documents, analyzing indices, and managing clusters.

Model Context Protocol (MCP): Open Standard for AI Integration

The Model Context Protocol (MCP) is an open standard enabling AI systems to connect with diverse data sources, tools, and services, eliminating custom integrations for seamless interaction.

Supabase MCP Server

Supabase MCP servers enable AI models to interact with Supabase backends, providing capabilities for PostgreSQL databases, real-time subscriptions, authentication, and storage operations.

Development Tools & DevOps MCP Servers