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CI/CD & DevOps

Continuous Integration and Continuous Deployment tools and workflows. Enables automation of software delivery pipelines, build processes, testing, and deployment operations.

MCP ServersBrowse all →

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    An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.
    Last updated
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    Apache 2.0
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    A Model Context Protocol (MCP) server for LocalStack that enables management of local AWS development environments, including container lifecycle operations, infrastructure deployments, log analysis with IAM policy generation, chaos injection, and Cloud Pods state management.
    Last updated
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    Apache 2.0
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    Enables interaction with the Tembo API to manage organization tasks and view enabled code repositories. Users can create, search, and list tasks or retrieve account information directly through MCP-compatible clients.
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    MIT
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    Enables AI assistants to interact with Sauce Labs testing platform through natural language, providing access to device cloud management, test job analysis, build monitoring, and testing infrastructure insights. Supports both Virtual Device Cloud (VDC) and Real Device Cloud (RDC) with comprehensive test analytics and team collaboration features.
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    Enables AI assistants to inspect, query, and diagnose problems within Octopus Deploy instances. Provides read-only access to deployments, releases, projects, environments, and other DevOps resources to transform AI into your ultimate DevOps wingmate.
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    Mozilla Public 2.0
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    Model Context Protocol (MCP) server for GitLab — exposes 1006 GitLab REST & GraphQL API operations as MCP tools (42 meta-tools / 57 enterprise), 24 resources, 38 prompts, and 17 completion types for AI assistants. Written in Go, single static binary, stdio and HTTP transport.
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    MIT
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    Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.
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    MIT
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    Enables comprehensive GitLab integration allowing LLMs to manage projects, issues, merge requests, repository files, CI/CD pipelines, and perform batch operations. Supports advanced features like AI-optimized summaries, smart diffs, and atomic operations with rollback support.
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    Apache 2.0
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    A local Python MCP server that exposes the Codemagic CI/CD REST API as Claude-callable tools. Trigger builds, manage apps, download artifacts, and clear caches — all from Claude Code or Claude Desktop without leaving the chat.
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    MIT
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    An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.
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    MIT
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    Connects AI tools directly to Codemend production error monitoring to list, analyze, and resolve software crashes. It enables users to retrieve AI-generated fixes and automatically open GitHub pull requests to address production issues.
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    MIT
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    A TypeScript-based MCP server scaffold designed for monitoring and interacting with Drone CI environments. It provides tools for webhook parsing, HMAC signature verification, and state management for CI/CD pipelines.
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    Apache 2.0
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    Enables AI assistants to interact with and manage Google Cloud Platform resources including Artifact Registry, BigQuery, Cloud Build, Compute Engine, Cloud Run, Cloud Storage, and monitoring services through a standardized MCP interface.
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    SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.
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    MIT
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    Enables management of Amazon Managed Workflows for Apache Airflow (MWAA) environments and operations including DAG management, workflow execution monitoring, and access to Airflow connections and variables through a unified interface.
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    Apache 2.0
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    Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.
    Last updated
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    MIT

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