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    An MCP server providing comprehensive Gitea API coverage with 186 tools for managing repositories, issues, pull requests, and CI/CD workflows. It enables autonomous AI agents to perform complex development and administrative tasks directly through a Gitea instance.
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    MIT
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    Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production. LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI. šŸ¤– Stops AI
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    MIT
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    Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.
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    Apache 2.0
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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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    Python MCP server for GitHub operations, providing native tool integration with Claude Code and other MCP clients. It enables managing issues, pull requests, CI status, milestones, and batch operations via natural language.
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    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.
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    A Bitbucket CLI and MCP server written in Go for managing workspaces, repositories, pull requests, pipelines, issues, and source code. Supports stdio and HTTP transport.
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    Apache 2.0
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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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    4
    MIT
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    Enables AI coding assistants to interact with JetBrains TeamCity CI/CD server through natural language commands. Supports triggering builds, monitoring status, analyzing test failures, and managing build configurations directly from development environments.
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    MIT
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    Enables monitoring and control of the SST development process by streaming dev logs, managing Lambda invocations, and executing lifecycle commands like start, stop, and restart. It provides real-time access to event streams and deployment status directly through the Model Context Protocol.
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    Agentic data quality MCP server — runs structured validation rules against warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres), diagnoses failures with LLM root cause analysis, and proposes SQL remediations. Full audit trail of every AI decision.
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    Apache 2.0
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    Integrates Ploi.io API functionality into AI assistants for managing servers, sites, and databases through natural language. It enables features like one-command deployments, project linking, server log retrieval, and database backup management.
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    MIT
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    Enables AI assistants to interact with Coolify for complete infrastructure management including applications, databases, servers, deployments, and team operations. Provides 100% API coverage with 64 tools for managing the entire Coolify ecosystem through natural language.
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    MIT