"Information about queue-based systems or concepts" matching MCP servers:

Enforces authorize-before-execute for any MCP-compatible AI agent. Exposes atlasent_evaluate and atlasent_verify_permit tools so a protected tool call only runs after AtlaSent issues and verifies a signed, single-use permit — fail-closed on any error, timeout, or malformed response.

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.

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.

Post-quantum readiness for AI coding agents: scans code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and returns NIST ML-KEM/ML-DSA/SLH-DSA (and hybrid) migration guidance, with fix verification and dependency checks. Content-based, advisory tools only; runs local (npx @quantakrypto/mcp) or as a hosted OAuth endpoint.

Enables AI assistants to create and validate workflow diagrams using FlowZap's text-based DSL. Generates shareable playground URLs for visualizing flowcharts, process diagrams, and CI/CD pipelines through natural language descriptions.

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.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

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.

Enables AI assistants to manage and operate Venelx CI/CD pipelines through the Venelx REST API, including listing projects, triggering builds, checking status, tailing logs, accessing artifacts and workers, and diagnosing signing or GitHub access.

MCP server that connects AI agents to Jenkins, supporting stdio and HTTP transports with tools for jobs, builds, logs, and queue management.

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

Enables managing GitHub Actions workflows through MCP, including listing and inspecting workflows, triggering workflow_dispatch and repository_dispatch events, and monitoring or canceling workflow runs.

Provides structured project management through phase-based workflows, enabling planning, execution tracking, compliance checking, and automated documentation for software development projects.

Connects AI assistants to GitHub Actions workflows to monitor CI/CD pipelines, view run logs, diagnose failures, and optionally trigger or manage workflows with granular permission controls.

Enables AI systems like Claude and Cursor to directly manage Railway projects, deployments, services, environment variables, and monitor logs through natural language commands.

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.

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.

A dynamic Azure DevOps MCP server that automatically switches authentication context based on the current working directory, enabling seamless integration with multiple Azure DevOps organizations and projects.

Enables SSH-based deployment operations such as git pull, command execution, script upload/run, and SSH config management.

Enables interaction with multiple Azure DevOps organizations simultaneously, providing access to pipelines, builds, repositories, and pull requests across different organizations without switching contexts or restarting the server.