"Lottery games and results" matching MCP servers:

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables Large Language Models to play chess agentically with real-time HTML board visualization and a hybrid AI engine featuring ten difficulty levels. It supports interactive games between users and agents, including a web dashboard to monitor active matches.

Turns any MCP-over-stdio client into a supervisor for a long-lived DeepSeek Harness coding agent: dispatch a goal, interrupt or steer it mid-flight, and collect results — with conversations that survive process restarts and crashes. Also supports running many conversations at once, approval round-trips, and completion notifications instead of polling.

An MCP server that enables natural language interaction with the Lichess chess platform, allowing users to play games, analyze positions, manage their account, and participate in tournaments through Claude.

A Model Context Protocol server that allows AI agents to play Texas Holdem poker games through an MCP client interface.

Lets an orchestrating agent spawn, queue, steer, and collect Codex agents through MCP tools, including resource claims, structured results, question handoff, and workflow scripts.

Enables creation and management of structured game worlds for text adventures and RPGs with character creation, world generation, and natural language interaction through AI integration.

Enables connecting chat channels to an Agent you control, letting authorized people assign work, steer ongoing tasks, and receive results directly from their chat app.

Connects MCP-powered AI agents to the decentralized Agent Network Protocol (ANP) for DID-based identity, agent discovery, and secure agent-to-agent communication.

An MCP server that lets agents claim, work on, and finish units of work in a coordinated fleet, with lease and heartbeat protection, plus tools for orchestrators to define work and collect results.

Enables web ChatGPT sessions to submit discussion results back to the original Codex task via MCP, allowing the task to continue after the web interaction completes.

An MCP server that uses Google Antigravity subagents as parallel workers for coding agents, enabling efficient task delegation with compact results.

Lets AI assistants use websites as callable tools in your signed-in browser, automatically learning site APIs from use and keeping context small with compact tool results.

Enables MCP-capable agents to check in, declare safe capabilities, receive bounded non-duplicative public-interest tasks, perform permitted work, and submit evidence or results for replication and improvement.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables running parallel subagents with configurable models and reasoning effort through a single MCP tool, collecting results in subtask order.

Enables coordinating specialist agents through an event-driven backend, allowing submission of goals, retrieval of job status and results, and listing of jobs via MCP tools.

Enables Claude Code to query Pi through a JSON protocol with nesting, hop limits, token budgets, session lanes, and cancellation, treating peer output as untrusted tool results.

A high-performance MCP server for browser automation via Chrome DevTools Protocol, enabling fast, low-cost, and anti-bot web interactions.

Implements a distributed AI worker pattern over MCP, enabling clients to register as workers, poll for tasks, process prompts with AI, and submit results back to the server continuously.

Enables multiple Claude Code sessions to communicate and share results automatically, with optional orchestration for hands-off workflow coordination.

Marketplace plugin enabling Claude Code to discover, hire, monitor, and retrieve results from remote agents via Agrenting, with scoped API keys and secure escrow payments.

Enables AI agents to securely reach enterprise tools and other agents through a governed gateway with pinned tool definitions, delegated authorization, content inspection, human approval, and signed audit trails.

Enables MCP clients to hand tasks to DeepSeek Harness as an execution subagent, creating sessions, submitting work, waiting for results, and retrieving outputs.

A server that enables document searching using Vertex AI with Gemini grounding, improving search results by grounding responses in private data stored in Vertex AI Datastore.

Gives coding agents a single search tool backed by a self-hosted SearXNG instance, parsing and scrubbing queries, merging duplicates, and ranking results with BM25F plus optional decision-model reranking. Returns compact, token-efficient results with relevance bands, engine warnings, and optional stop/refine/broaden hints.

Enables Claude or other MCP-compatible models to delegate tasks to Grok Bot on a cloud computer, automatically waking it if needed and returning execution results for multi-turn collaboration.

Enables enterprise MCP clients and partner agents to execute tenant-isolated underwriting, claims, and compliance workflows with durable step checkpointing, evidence-grounded tool calls, and deterministic PDF citation receipts. It supports A2A task dispatch and MCP JSON-RPC operations while blocking cross-tenant access and ungrounded deliverables.

Provides a deployable remote MCP server that serves interactive HTML widgets alongside tool results, enabling agent plugins for Cursor, Codex, and Claude Code.

Enables MCP clients to perform speculative tree-search action prediction and prefetching using Laplace-smoothed Markov transitions, returning deterministic JSON tool results.