"The most widely used models" matching MCP servers:

. A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{

Enables AI assistants to manage website deployments over SFTP/FTPS by listing sites, testing connections, comparing files, previewing changes with approval tokens, creating SHA-256 verified backups, and executing authorized uploads.

MCP server for DCI API enabling AI models to extract and analyze DCI jobs, components, and topics, with integrations for Google Drive, Jira, GitHub, and Red Hat support cases.

Lets MCP clients such as Claude or ChatGPT find the pull requests waiting on your review, read their details and changed files, check CI status, post comments, and submit approve, request-changes, or comment reviews. It runs locally over stdio with a personal token or as a remote server with its own OAuth 2.1 authorization server (PKCE, dynamic client registration, per-client consent, and refresh-token rotation) so GitHub is only used to sign the user in.

A local MCP server that packages LLM evaluation gates as reusable CI/CD primitives, enabling AI agents to run datasets against models, score responses, and enforce quality thresholds.

An MCP (Model Context Protocol) server that integrates with the ArgoCD API, enabling AI assistants and large language models to manage ArgoCD applications and resources through natural language interactions.

A git-native merge gate. mergelock check compares two branches before they meet and reports the conflicts git itself won't tell you about: a function whose signature changed on one branch while the other branch added calls to the old signature, a symbol deleted on one side but still used on the other, the same function written twice.

Self-hosted coding agent that runs Claude Code or Codex in your own infrastructure and works from Slack. Exposes codebase investigation, file edits, branch and PR creation, allowlisted command execution, CI status and an audit log as MCP tools, keeping every credential behind the tool layer instead of handing it to the model.

A local MCP server for Jenkins that provides 17 tools to interact with Jenkins jobs, builds, logs, SCM, and test results via REST API, no plugin required.

Provides Xcode build, test, and package management operations through the Model Context Protocol.

Enables AI assistants to review GitLab merge requests by fetching changes, analyzing diffs, adding comments, and managing approvals through the GitLab API. Supports complete merge request analysis, file-specific reviews, and version comparisons.

The most comprehensive Azure DevOps MCP server & CLI — 13 tools, 82 actions, single Go binary.

Enables headless Blender asset QA and FBX reimport verification for game and 3D asset pipelines, checking mesh count, material count, and naming prefixes with deterministic JSON results.

The Model Context Protocol (MCP) Jenkins integration is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

Enables interaction with Gerrit code review system via REST API, allowing language models to query changes, retrieve details, and manage reviews.

Enables orchestrating secure software development pipelines with domain-specific compliance (HIPAA, PCI-DSS, etc.), generating pseudocode, threat models, and CI/CD from user stories via natural language.

MCP server for GitLab that provides 85 tools covering issues, merge requests, repositories, CI/CD, wiki, packages, and attachments, with support for both gitlab.com and self-hosted instances. It can read attachments so models can see screenshots and other files.

Unified capability catalogue with formally verified cartridges, distributed community hosting, and the Teranga menu system for single gateway access to a vast rabbfe of MCP, LSP, NeSy and related servers.!

Exposes all Dokploy API endpoints as MCP tools, enabling AI models and other clients to manage projects, applications, databases, and more on a Dokploy server.

Enables AI assistants to deploy and manage hosted apps from git repos, read logs, add Postgres databases and domains, manage API keys and budgets, and send requests to 200+ AI models. Connects over remote Streamable HTTP with OAuth sign-in, so users need no API keys, installs, or local server.

Enables AI assistants to manage Prismatic integrations, components, and flows via the Model Context Protocol, supporting code-native integration development and component lifecycle.

Enables AI assistants to interact with the Cycloid platform for infrastructure management, including blueprint discovery, stack creation, pipeline listing, and event monitoring via natural language.

Maestro is the simplest and most effective UI testing framework for Mobile and Web. Maestro MCP allows you to control emulators, interact with apps, write and automatically debug UI tests on Claude Code, Cursor or Windsurf.

Deploys the current folder or a GitHub repo to a live HTTPS URL on Dockhold, and lets AI tools read status/logs, set variables, and resize apps and managed databases.

Publish websites from Claude, the terminal, or CI — drop a folder, get a link that doesn't expire. Wraps the nippy.host publish pipeline: create sites, update in place, read files, passwords, SEO settings, and visitor analytics.

Serves MoleSignal's tools over stdio to AI agent tools such as Claude Code, Cursor, Codex, VS Code, or Gemini CLI, enabling them to query logs, metrics, traces, incidents, approvals, deployments, and other capabilities under the user's permissions and organization policy.

Enables connecting your service to the LAF bot by providing a minimal MCP server that reports critical signals and additional risk-annotated tools, with built-in submission checks and CI.

Budget & cost control for AI agents: hard per-agent spend caps, rate limits, idempotency, and human-in-the-loop approval — enforced before each LLM call, not after the invoice. One hosted MCP endpoint (no proxy or self-hosting), settled via x402 (USDC on Base).

Local MCP server enabling agents to track Xcode Cloud builds and access TestFlight crash reports through the App Store Connect API.

Suggests the latest stable package versions when writing code.