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"Database reading and data retrieval" matching MCP servers:

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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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    Blocks unsafe PostgreSQL migrations before an AI agent writes or runs them. check_before_apply returns a pass/fail gate; reads the real Postgres parser, classifies the lock each statement takes, checks 112 safety rules. Runs offline, no database required.
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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 monitoring and analysis of Ansible playbook executions through the Ara Records API. Provides real-time playbook monitoring, task progress tracking, and comprehensive access to Ansible execution data.
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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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    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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    MCP server for Sqemo, a web-based ERD tool with team naming standards. 34 tools: read/edit entities, attributes, and relationships; generate physical names from a shared glossary and naming rules; SQL (7 dialects) and DBML import/export; ERD lint, diff, and ALTER generation.
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    MIT
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    Enables searching, reading, and analyzing discussions on GitLab's community forum for troubleshooting CI/CD issues and GitLab features. Pre-configured with GitLab-specific search filters and optimized workflows for support scenarios.
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    MIT
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    Enables comprehensive Jenkins automation through MCP interface, allowing users to manage builds, jobs, artifacts, and queues with natural language commands. Supports build triggering, monitoring, artifact retrieval, and system status checks with automatic CSRF protection and authentication.
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    MIT