"Orbit Sentinel - Satellite or Space Monitoring System" matching MCP servers:

MCP server for JetBrains Space merge requests and Patronus CI dry runs, enabling creation, viewing, and management of merge requests as well as starting and monitoring CI dry runs.

Security auditor for CI ecosystems that detects supply-chain and injection flaws in CI/CD configuration files across seven CI platforms, providing taint analysis, remediation, and compliance scoring.

A continuous, out-of-band trust and reliability layer for the MCP ecosystem. It fingerprints MCP server tool definitions, detects and classifies drift (e.g., rug pulls) via a severity taxonomy, maintains a hash-chained evidence ledger, and gates CI with SARIF—while also acting as an MCP server itself so agents can check a server's safety before binding.

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

Analyzes Git pull request diffs to detect breaking REST and GraphQL API schema changes, providing deterministic AST-level code review and breaking change alerts for CI/CD workflows.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.

Zero-config data quality monitoring as MCP tools. Profiles a warehouse (Postgres, BigQuery, Snowflake, MySQL, DuckDB), detects anomalies, and gates CI — read-only with the connection resolved server-side, never via the model.

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.

Enables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.

MCP server and CLI for AlmaLinux Build System (ALBS) that enables AI coding assistants to investigate build failures, create builds, sign packages, and manage release plans through natural language.

An intelligent MCP server that gives AI agents full control over GitHub Actions CI/CD pipelines, including real-time monitoring, log analysis, AI-powered failure diagnosis, and deployment management.

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.

Enables AI assistants to manage CData Sync operations, including data synchronization jobs, connections, and ETL processes through stdio or HTTP transports. It provides tools for executing jobs, monitoring real-time progress via Server-Sent Events, and handling comprehensive workspace configurations.

Enables management of Railway.app infrastructure through natural language, including deploying services, managing environment variables, monitoring deployments, and handling databases and volumes.

MCP server for Beaker lab automation, enabling system provisioning, job management, distro discovery, and failure diagnosis through 25 tools.

Enables management of Railway.app infrastructure through natural language, including deploying services, managing environment variables, monitoring deployments, and controlling project resources.

Enables monitoring and debugging of Hatchet workflows and jobs through MCP clients like Claude Code. Users can list workflows, track run statuses, query queue metrics, and retrieve job results using natural language commands.

A local MCP server that exposes Bazel build system capabilities to AI assistants.

A local MCP server that exposes Blacksmith.sh's usage and cost data, enabling queries for CI spend through agents, alerts, or dashboards.