"Finding at least 10 personal assistant Minecraft servers" matching MCP connectors:

Personal-finance workspace for AI agents: accounts, spending, budgets, goals, and investments.

Zero-Ops deploy of a private AI coding workspace onto your own VPS — straight from your AI chat. Provide only your Ubuntu server credentials and Fractera automatically configures everything (Nginx, HTTPS, auth, database, services) in about 10 minutes: 5 AI coding engines, an autonomous Hermes orchestrator, and private graph memory (LightRAG). No terminal, no DevOps. IP-first and free; a custom domain with HTTPS is an optional later step.

Draft a bilingual wedding invitation website with RSVP and meal choice. Creates an unpaid draft with a live preview URL; publishing needs a human checkout, so an assistant cannot put the site live or spend money. No account and no credentials.

Recurring agent jobs that run on our servers and ping you only when the result changed.

A registry of AI agent tools — MCP servers, APIs, CLIs, SDKs — kept current by automated ingestion.

Discover x402 services, MCP servers and A2A agents by intent — agent-tools.cloud directory.

Search 150k+ AI agents and MCP servers. Live liveness probes, behavioral benchmarks, x402 commerce.

Search agents & MCP servers by capability, with daily-observed pricing, liveness and market data.

Search, vet & assemble MCP servers from your agent: verified tools, risk labels, and trust scores.

Agent-native catalogue of Baseframe Labs dev tools and MCP servers.

Hosted MCP server for noticed. Exposes ~50 noticed agent capabilities (network search across GitHub + LinkedIn, missions, PRM, memory, workspace, web search, cron, ...) via two meta-tools — search + execute. Bearer-API-key auth; key minted at noticed.so/dashboard/api-keys.

Open execution contract for agents doing business work. 6 operators following one spec. Approval-gated, tenant-isolated, MIT. Reference at chieflab.io/spec/v0.1.

Trust, freshness, policy, and discovery layer for public MCP servers.

The Remote MCP server acts as a standardized bridge between LLM applications (like Claude, ChatGPT, and Cursor) and external services, enabling AI agents to access external tools and resources. Its primary capability is providing a centralized search tool to discover other MCP servers and their respective tools. Unlike local implementations, it runs remotely with OAuth authentication and permission controls for security.

The Google Compute Engine MCP server is a fully-managed Model Context Protocol server that provides tools to manage Google Compute Engine resources through AI agents. It enables capabilities including instance management (creating, starting, stopping, resetting, listing), disk management, handling instance templates and group managers, viewing machine and accelerator types, managing images, and accessing reservation and commitment information. The server operates as a zero-deployment, enterprise-grade endpoint at https://compute.googleapis.com/mcp with built-in IAM-based security.

Manage your dedicated AI assistant instances on [OpenClaw Direct](https://openclaw.com) through natural language. Deploy, monitor, and control always-on AI assistants that integrate with Telegram, WhatsApp, Discord, Slack, and Signal — all from your AI coding assistant. Learn more about the [MCP integration](https://openclaw.com/openclaw-mcp-integration).

Remote MCP + A2A server for AI agent operations. Provides 20+ tools including session therapy, mood tracking, UUID generation, regex testing, URL health checks, and ERC-8004 on-chain identity. Hosted at api.delx.ai with REST, MCP (SSE/streamable HTTP), and A2A protocol support.

Secure every MCP server with one governed gateway. Give each AI agent its own scoped MCP access, contain credentials at the gateway, and audit every MCP tool call without wiring agents directly to each server.

An API for forecasting and multi-agent research. FutureSearch provides endpoints that use web research agents at scale, for higher accuracy than web search or single agent approaches alone can achieve. forecast runs a team of forecasters to predict future dates, numbers, and probabilities. multi_agent orchestrates multiple researchers to answer one question. agent_map runs one research agent over every row of a dataset, scaling to thousands of rows and agents.

Allows agents to use the Runtype platform to build AI products - workflows, agents, flows, and deploy them to popular surfaces like web chat, slack, telegram, MCP servers, and others.