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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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    Local-only GitHub Actions and CI maintenance scanner for AI-built apps. Exposes scan, explanation, and fix-planning tools to MCP clients; modifies nothing and makes no outbound requests by default.
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    MCP server for Bitbucket Cloud that enables reviewing, managing, and merging pull requests, assigning reviewers by name, reading files at a ref, and inspecting pipeline status from any MCP client.
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    MIT
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    Enables natural language interactions with CircleCI through Model Context Protocol, allowing users to retrieve build logs, find flaky tests, check pipeline statuses, and manage workflows without leaving their IDE.
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    Apache 2.0
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    A GitHub-native secrets manager that allows AI assistants to securely manage, generate, and validate credentials without exposing sensitive values in conversation history. It supports secret scanning, environment diffing, and secure command execution by injecting masked variables directly into the runtime environment.
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    Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.
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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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    Enables AI assistants to review GitLab merge requests by fetching changes, analyzing diffs, adding comments, and managing approvals through the GitLab API. Supports complete merge request analysis, file-specific reviews, and version comparisons.
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    Enables AI assistants to manage development workflows by running build commands, executing tests, analyzing package.json files, installing dependencies, and performing code linting. Supports multiple package managers (npm, yarn, pnpm) and provides detailed error reporting for development operations.
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    A Python MCP server that wraps the GitHub CLI (gh) to provide structured tools for searching, reading, and managing GitHub resources like repos, issues, PRs, releases, and workflows, with write commands disabled by default.
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    Exposes open automation platform capabilities to AI agents with tools for managing job templates, inventories, collections, EDA activations, audit events, and policy checks, governed by gateway auth, RBAC, and policy enforcement.
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    MCP server for Coolify API that enables full deployment workflows from zero to production, including project, server, and application management.
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    MIT