"Google Calendar MCP" matching MCP servers:

An MCP server that drives Google Play releases: bundle upload, track releases (internal/closed/open/production), listing metadata, store graphics, and review replies.

Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.

Enables AI assistants to interact with and manage Google Cloud Platform resources including Artifact Registry, BigQuery, Cloud Build, Compute Engine, Cloud Run, Cloud Storage, and monitoring services through a standardized MCP interface.

Enables autonomous AI agents and developers to programmatically manage Google Play apps via the Play Developer API v3, including uploading Android App Bundles, managing release tracks, updating store listings, and replying to user reviews.

Manages Google Play Store listing text through the official Android Publisher API with dry-run-first safety, supporting CLI for humans/CI and MCP tools for agents.

Enables intelligent management of Google Cloud Platform infrastructure using Terragrunt, with support for experimental stacks, parallel deployments, resource visualization, cost analysis, and comprehensive infrastructure operations through natural language.

Enables AI agents to automate Android release workflows via the Google Play Android Publisher API, including deploying builds, managing listings, and replying to reviews.

A Google Cloud MCP server that enables users to manage Cloud Build and Cloud Run resources. It allows for listing builds and services, as well as retrieving detailed logs and execution status.

Google Play Console MCP server — lets AI agents manage releases, track rollouts, reply to reviews, and pull crash/acquisition reports directly from Google Play Console.

MCP server for managing Google Play app deployment and in-app products via the Android Publisher API v3.

Exposes Jenkins CI/CD capabilities as MCP tools, including job management, builds, pipelines, and Terraform/GCP log inspection.

Provides AI assistants with access to Capawesome documentation and Cloud management tools, enabling app, build, and deployment operations via API token authentication.

Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.

Agent-readiness scorecard for any MCP server: protocol checks, 0-100 score and actionable findings.

Checks npm and PyPI packages for outdated versions, deprecation status, and breaking changes with cited sources, enabling AI agents to verify dependency freshness.

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.

Connects AI coding assistants to Gaffer test history and coverage data to analyze project health, debug failures, and identify untested code areas. It enables tools to track test stability, cluster failures by root cause, and monitor code coverage trends across projects.

A security-focused MCP server for self-hosted n8n Community Edition, providing 44 bounded tools to manage workflows, nodes, executions, credentials, tags, and more via the n8n Public API.

Enables AI assistants to monitor GitHub repository health by calculating health scores, fetching repository metadata, analyzing Dependabot alerts, checking CI/CD status, and retrieving code scanning alerts.

Enables AI agents to deploy HTML and pull reviewer comments via the briefroom CLI without spawning shells.