"Information or uses related to a rag" matching MCP servers:

An MCP server that adds engineering discipline to AI-assisted development, enforcing evidence-gated TDD, security review, backup strategy, and deployment generation to turn AI-generated code into production-ready software.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

This MCP server enables intelligent API testing automation by combining RAG knowledge retrieval with tool execution capabilities. It allows QA engineers to perform natural language-driven API testing with contextual knowledge support.

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.

Enables AI coding agents and CI to vet npm dependencies before they reach the lockfile, flagging hallucinated, slopsquatted, or otherwise risky packages with evidence-backed verdicts.

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.

MCP server for publishing HTML or Markdown to a live hosted URL via htmldrop. Provides tools to publish, list, and delete hosted sites, with remote OAuth and API token authentication.

Provides MCP tools to get a single-call snapshot of git and GitHub Actions CI status across all repositories in a folder, flag missing or stale architecture docs, write doc files, and detect release drift between source and release repositories.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

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.

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.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

A Model Context Protocol server that monitors shadow-cljs builds and provides real-time build status updates for ClojureScript projects, allowing LLMs to verify build status after making code changes.

Enables code-review gating by converting a git diff into a typed verdict with safety probabilities, severity, and recommended actions for auto-merge or human review.

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

Publishes normalized release notices to a configured webhook via MCP, with built-in validation, deterministic dry-run mode, and a clear boundary for authority gates.

Enables deployment and management of applications on the Citizen platform from git repositories or local files. It allows AI assistants to monitor deployment logs, handle authentication, and automatically fix build errors using intelligent error analysis.