"Information about Gmail MCP Node" matching MCP servers:

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

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.

Enables reviewing GitHub Actions workflows for outdated actions, deprecated Node runtimes, retired runners, deprecated commands, and security risks, with file, line, and fix for each finding.

Enables coding agents and CI/CD pipelines to audit untrusted code by detecting Python sandbox escapes, SQL injection taint, ReDoS regex vulnerabilities, and CORS misconfigurations, while generating Seccomp BPF filters for safer execution.

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.

Renders an interactive pipeline DAG and test-harness dashboard inline in MCP hosts, showing node statuses, pass rates, costs, and latency from a JSON state file.

Enables retrieving comprehensive information about GitLab merge requests, including details, commits, diffs, discussions, approvals, and CI/CD status, through natural language.

Enables AI assistants to answer questions about nixpkgs packages using nixkeeper's public data, covering outdated versions, Hydra build status and failures, update-bot attempts, related PRs and issues, CVEs, and what needs attention for a maintainer or team. It runs locally over stdio, reads only public data, and requires no account or token.

A git-native merge gate. mergelock check compares two branches before they meet and reports the conflicts git itself won't tell you about: a function whose signature changed on one branch while the other branch added calls to the old signature, a symbol deleted on one side but still used on the other, the same function written twice.

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.

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.

Enables interaction with Blacksmith CI analytics to query workflow runs, jobs, test results, and usage metrics. It provides detailed access to CI/CD data including job logs and billing information directly through Claude.

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.

A comprehensive MCP server with 53 tools for managing Jenkins CI/CD operations, including job, build, pipeline, node, credential, and plugin management, enabling AI assistants to control Jenkins servers through natural language.

A Model Context Protocol server that allows management of Netlify sites, enabling users to create, list, get information about, and delete Netlify sites directly from an MCP-enabled environment.

A Model Context Protocol server that enables integration with GitHub Actions, allowing users to fetch available actions, get detailed information about specific actions, trigger workflow dispatch events, and fetch repository releases.

Enables AI assistants to interact with Terraform Cloud workspaces and runs, including checking run status, listing workspaces, and retrieving detailed information about workspaces and runs.

Generates VS Code installation buttons and markdown badges for MCP servers, supporting both Stable and Insiders versions with configurable inputs and commands.

Enables coding agents to develop on one machine and verify results on another, using branch-bound runbooks, isolated checkpoints, and structured receipts to guide repair iterations.

Enables deploying and managing projects across AWS, Google Cloud, Azure, DigitalOcean, Hetzner, and Vercel directly from Claude Code, with tools for instance lifecycle, domains, environment variables, backend services, databases, webhooks, and GitHub integration.

Give your coding agent the dependency graph it is about to change: scan, diff, explain, audit.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

Enables automated analysis of Woodpecker CI pipeline failures with intelligent error detection and fix suggestions. Supports both direct pipeline analysis and IDE-integrated git-context analysis using repository names, PR numbers, or branch information.

Enables comparing local and CI environment descriptors to report differences in Node version, OS, lockfile presence, and environment variable keys—including changed values by key only—without echoing secret values.

An MCP server for automated code reviews on Azure DevOps pull requests, enabling AI assistants to fetch PR details, validate requirements, post inline comments, and set review votes.

Enables automated Python code quality checks including linting, complexity analysis, typo detection, structure validation, duplicate detection, and test coverage, with integration into Cursor IDE and CLI.

Enables AI assistants to list and retrieve repositories, fetch and create pull requests, and access pipeline information through cloud and server APIs with configurable authentication.

Builds a dependency and topology graph of a Kubernetes/FluxCD GitOps repository via static analysis, enabling AI agents to reason about service relationships without cluster access.

Enables AI agents to query and interact with Azure DevOps data, including work items, projects, ticket statistics, and backlog information through natural language commands.