"General information or resources about data" matching MCP servers:

Enables running SQL warehouse validation checks through natural-language questions in MCP clients, while reusing the same logic for automated pipeline and CI/CD runs.

Enables developers to manage Genesys Cloud Function Data Actions through natural language in Cursor, including validating, building, planning, and applying function deployments while enforcing safety controls like plan-before-apply and read-only mode.

MCP aggregator with many existing NCP templates and allows running external MCP servers too

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Enables AI agents to deploy static files and get live HTTPS URLs instantly, with support for custom domains and data residency.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

Detects breaking changes in a TypeScript library's public API and recommends the semver bump, comparing two npm releases, git refs or a working tree. Each finding is graded proven or review-only.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

An MCP server that lets AI assistants manage KubeAid GitOps clusters, inspecting ArgoCD apps, pods, events, and resources, with optional write operations like syncing apps and scaling deployments through your own kubeconfig credentials.

Analyzes database migrations for risks like lock contention and data loss before they run. Supports Flyway and Liquibase formats, providing risk scores and rollback generation.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Lets any MCP-capable client connect to the public Codemagic REST API to list apps and teams, inspect build history, and optionally trigger or cancel builds and manage team settings. Runs locally over stdio with the user's own API token and configurable read-only, build, or administrative permission modes.

Aegis keeps Claude Code, Codex CLI and Antigravity on your project's rules via a zero-dependency Model Context Protocol (MCP) server (aegis-mcp), AGENTS.md / CLAUDE.md bootstrap, git pre-commit hooks, and CI governance (aegis check). It serves each agent just-in-time rules for the files it is about to edit, then enforces AST and repository invariants before commit and in pull requests.

Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.

MCP server that automates the publishing and validation of Tableau workbooks and data sources on Tableau Server or Tableau Cloud, enabling an AI agent to discover, build, validate, and publish content without human intervention.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

Enables AI assistants to deploy and manage SnapDeploy containers and resources—including builds, logs, environment variables, databases, and custom domains—directly through natural language.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Enables management of Railway.app infrastructure through natural language, including deploying services from GitHub repos or Docker images, managing environment variables, monitoring deployments, and configuring networking and volumes.