"Lottery games and results" matching MCP servers:

Delegates coding tasks to the locally installed DeepSeek Harness CLI, enabling MCP clients to run prompts through dsh and receive results with exit code and timing.

Enables OpenAI Codex to delegate tasks to Google Antigravity CLI, running them headlessly and polling for results.

AgentBridge is a local MCP server that lets Claude Code delegate coding tasks to external CLI workers like Codex and Antigravity. It assembles structured prompts, runs the workers with git snapshotting, and returns compact structured results without running its own models.

Enables running SPICE netlists with ngspice in batch mode and returning .meas results as JSON.

An MCP server that wraps Flutter CLI tools into structured, agent-friendly tools for AI coding agents, with features like two-phase test results, output capping, and managed app lifecycle.

Enables AI assistants to execute SQL queries against any database supported by the usql CLI tool. Provides seamless database interaction through MCP by forwarding queries directly to usql and returning results in JSON or CSV format.

Enables AI clients to securely execute remote commands and transfer files over SSH through standardized MCP tools, with multi-host management, flexible authentication, and an admin console.

Voice-driven CFD MCP server that enables natural language setup, execution, and analysis of OpenFOAM simulations, with results exportable to ParaView.

Enables AI to present options and launch an interactive web or terminal interface for user selection, then return the results to the AI.

Enables AI assistants to delegate complex tasks to the local Gemini CLI, returning structured results with execution metadata.

A Model Control Protocol server that provides access to nmap network scanning functionality, allowing users to run customizable scans, store results, and analyze network security using AI prompts.

Provides Claude with direct access to the Open Porous Media (OPM) reservoir simulation stack, enabling running simulations, inspecting results, and automating workflows via natural language.

A CLI command execution server that enables running shell commands with structured output, providing detailed execution results including stdout, stderr, exit code, and execution duration.

Enables natural-language automation of LS-PrePost preprocessing and postprocessing by exposing tools that build and verify shell meshes, query nodes, parts and connectivity, run native commands, SCL and in-application Python, and read d3plot/binout results through pluggable backends. Every job runs in its own directory and returns an ID, status, log and artifacts, so results stay traceable and failures are never silently reported as success.

Enables AI coding agents and MCP clients to run a read-only environment check against a project's declared requirements and receive structured results identifying exactly what needs fixing.

Exposes four stdio tools that let an agent research an application's documented interface, produce a validated single-use plan, and execute read-only operations against public HTTP JSON APIs, static HTML/JSON/text sources, and host-configured CLIs. Runs in-process with no listening port, accounts, or model dependency, returning bounded results while keeping inputs and outputs inside a host-enforced research-plan-execute lifecycle.

A local-first tool to check public ECZ-ID Resolver posture, classify targets, and report deterministic results with routing.

Enables Codex to delegate coding tasks to a locally installed AI coding CLI over MCP, returning results, cost and turn metadata, and reusable session IDs for follow-up work.

Provides AI agents with an unrestricted VPS root shell by executing arbitrary shell commands and returning structured results such as exit code, stdout, stderr, timeout, and truncation status.

Enables AI-driven WinDbg kernel debugging via the Model Context Protocol, allowing agents to send debug commands and receive results.