"Importing FastMCP from the mcp.server Python Module" matching MCP servers:

Enables creation and management of Terraform modules for Facets.cloud infrastructure with interactive generation, validation, forking, testing, and deployment workflows through secure file operations and FTF CLI integration.

Provides Azure DevOps integration through MCP, enabling management of projects, work items, teams, and policies via natural language. Supports bulk work item creation with hierarchical relationships and iteration assignments.

Paid remote MCP for hosted MCP server providing structured receipts, usage logs, and audit-ready evidence for agent and CI workflows.

A production-ready MCP server template that enables developers to quickly build and deploy MCP servers with dynamic tool/resource loading, YAML-based prompts, and seamless OpenShift deployment. Supports both local development with hot-reload and production HTTP deployment with optional JWT authentication.

A DevOps-friendly template for building MCP servers with CI/CD, Docker support, and automatic documentation generation using fastmcp and FastAPI.

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 managing SAP Cloud Integration iFlows, packages, configurations, deployments, and runtime artifacts via natural language through the OData API.

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

Generates a daily standup note from GitLab merge request or GitHub pull request state: what is ready to merge, what is blocked, what is stale, and what is waiting on your review. When CI is red it opens the failed job's log and reports the error lines, so the note says why the pipeline failed rather than just that it did.

Self-hosted, multi-zone MCP server for GKE/EKS: git repo of Python tools → canary-deployed Rust+Python workers, OAuth sign-in, roles per group.

Enables AI coding tools to scaffold, build, and deploy Node.js or Python apps to Varity with a single command, automatically provisioning databases and backend services.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

MCP server for GitLab CI/CD — pipelines, jobs, schedules, branches, tags, merge requests and repository files. Works with any GitLab (SaaS gitlab.com or self-hosted) via python-gitlab.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.

Enables AI agents to retrieve the latest semantic version tags for container images from Docker Hub, GHCR, Quay, and other OCI registries, allowing them to pin specific versions for reproducible deployments.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.

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

CI health reports for GitHub Actions: flaky tests named from logs, wasted compute priced in dollars, zombie crons, PR feedback time, plus 21 lint rules with safe auto-fixes. Read-only MCP tools wrap the same Go binary.