"Remote MCP servers without authentication" matching MCP servers:

A Model Context Protocol (MCP) server that enables remote access to OpenCode AI coding agent, allowing MCP-compatible clients to leverage OpenCode's capabilities.

Enables AI clients to securely inspect and edit approved code, use semantic code intelligence, run builds/tests, supervise bounded processes, inspect Git, and execute owner-approved SSH commands on engineering workstations.

Enables agent-style remote development over SSH with file operations and command execution, exposing native tools for searching, editing, and transferring files on remote machines.

An MCP server that allows coding agents to search the Swift Package Index and retrieve GitHub READMEs without requiring an API key. It features comprehensive search filters for stars, platforms, and licenses, providing token-efficient responses optimized for LLM comprehension.

Simple sequential thinking MCP in python

A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools. Developed by Mammoth Growth.

Enables remote control of AI coding assistants (Claude Code/Codex) via Telegram, allowing you to manage long-running tasks, send commands, and receive notifications from anywhere. Supports unattended mode with smart polling for up to 7 days and multi-session management.

Wraps the local Qoder CLI into an MCP server, enabling any MCP client to delegate coding tasks to a local Qoder agent with session management, sandboxed permissions, and model selection.

Delegate tasks from Claude Code to other models (Codex CLI, DeepSeek, OpenRouter, etc.) without leaving the app.

Wraps the Claude Agent SDK as MCP servers, letting you spawn multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

A secure, containerized workspace for LLMs to autonomously code, test, and debug projects without risking the host machine.

Provides AI coding agents a full abap2UI5 development loop—writing ABAP classes, validating views, deploying, and running apps headless with screenshots—all locally without an SAP system.

A secure MCP server that gives AI coding assistants direct access to the shadcn/ui registry, enabling fetching, installing, and wiring up components without switching context.

Enables handing one self-contained job to the Claude Code CLI on the local machine and getting back its final message plus a manifest of the artifacts it produced, without letting Claude write into the user's project. Reads are limited to named directories and all writes stay in a throwaway run directory, so the user reviews the listed files and copies in only what they approve.

Provides per-Subagent MCP controls to any coding agent or client across all your MCPs and prevents context window waste. Loads only 3 tools instead of all your MCP Server's tool definitions. Agents discover tools on-demand, only when needed and only the servers and tools they are allowed.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

An MCP server that enables local AI models to receive guidance from remote 'senior' AI providers like OpenAI, Anthropic, and Gemini to solve programming problems. It features intelligent multi-turn dialogue management, context synchronization, and automated session history tracking.

Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

Enables any LLM to drive your local Codex CLI in a sandboxed workspace, running coding tasks and generating images without needing an API key.