"Latest Breaking News and Hot Topics" matching MCP servers:

A simple server that acts as a Master Control Program (MCP) for unified interaction with OpenAI and Anthropic (Claude) AI models through a single API endpoint.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Enables AI coding agents to compile, test, run, hot-swap, and debug Java applications incrementally through MCP, providing runtime feedback for verifying code changes.

Guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP tools for each stage, with confidence scores and rationales for tool suggestions.

Enables AI assistants to interact with running games in real time — introspecting game state, simulating keyboard and mouse input to actually play, capturing screenshots, executing Lua code, hot-reloading files, and receiving push notifications when state changes.

An advanced MCP server for real-time worldwide stock market data, technical indicators, financials, news, and Python sandboxing with AI models, supporting US and Indian markets.

Interactive algorithm coach MCP server that provides guided practice, local code execution, and real-world engineering case mapping for 45 algorithm topics.

MCP server for interacting with fal.ai models and services. Uses the latest streaming MCP support.

Enables pre-execution security checks and sandboxed execution for AI agent workflows, including prompt-injection detection, MCP rugpull and sampling abuse protection, untrusted tool-output sanitization, loop circuit breaking, SQL AST validation, PII redaction, and ephemeral Python execution.

Integrates Cursor AI with Vite Dev server, allowing AI agents to modify code and observe live updates through the Hot Module Replacement system in real-time.

A minimal MCP server template with hot reload support that helps developers quickly set up and build Model Context Protocol servers with example tool implementations.

Enables AI agents to launch, inspect, control, debug, and hot-reload live Mengine game builds through Visual Studio Code or standard MCP clients.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables MCP clients to list configured Python and Shell script routes and execute them with positional or named arguments over Streamable HTTP, returning stdout, stderr, status, exit code, and timeout details. It uses the same API-key authentication and hot-reloaded route configuration as the HTTP API.

Suggests the latest stable package versions when writing code.

Acts as an AI Gateway for MCP servers using Azure API Management, implementing the latest MCP Authorization specification.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

This MCP server enables coding agents to inspect and control live browser tabs, including evaluating JavaScript, outlining and interacting with the DOM, taking screenshots, reading console and network logs, and installing hot-reloaded userscripts.

Enables an authenticated persona to run OpenAI Codex coding tasks in an isolated per-user workspace checked out from a configured GitHub repository, with the work committed locally and published to a dedicated work branch. Also exposes task status for the latest run.

An MCP server that implements iterative refinement of responses through self-critique cycles, breaking the process into discrete steps to avoid timeouts and show progress.

A hot-reloadable MCP proxy server that enables users to create and manage custom Python tools through dynamic module loading. Users can build their own utilities, wrap APIs, and extend functionality by simply adding Python files to designated folders.

A hot-reload development tool that enables real-time development of MCP (Model Context Protocol) servers by automatically reloading tools as they're modified without requiring manual restarts.

Public implementation of MCP for ROS 2 enabling to interact with system visible various robots, capable of: List available topics List available services Call service Subscribe topic to get messages Publish message on topic and more

Exposes a stdio JSON-RPC tool surface that lets AI agents control running Flutter and Dart apps — starting, stopping, reloading, and hot-restarting sessions, reading logs, running doctor/list/tinker checks, and invoking plugin-contributed tools. It gives agents one shared protocol instead of ad hoc shell scripts.

Enables AI agents to write and debug World of Warcraft: Infinite addons end-to-end: statically checking Lua, .toc and XML against the client's own API manual, hot-loading changes into the running game, then executing Lua or slash commands and reading back errors with stacks, print output, events, frame info and screenshots. Also records events, inspects frames and keeps versioned history with one-click rollback.

Hardened MCP bridge to the full Ollama ecosystem — local and cloud models. 6 tools covering health, model management, chat, and generation with SSRF mitigation, singleton HTTP client, and structured error handling. Two deps, one file.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.

MCP server that gives AI assistants a secure gVisor-isolated sandbox to run Python or JavaScript code, returning stdout, stderr, and exit codes without local access.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.