"A server for making money" matching MCP servers:

前端ai主导的全流程，自动化的预开发；旨在解决前端开发在联调前期的各种繁琐工作

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

基于MCP架构的微信公众号文章爬虫系统，支持AI智能体通过Selenium自动抓取微信公众号文章内容和图片，实现文章内容的智能分析。

Enables real-time user intervention for MCP agents through a web UI, allowing users to review context and provide feedback when AI agents drift from intent, keeping them on track.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

Multi-agent swarm orchestrator for AI workflows. Exposes blackboard read/write, agent dispatch, permission gating (AuthGuardian), token budget enforcement (FederatedBudget), and audit log tools over MCP. Supports 14 AI framework adapters including LangChain, AutoGen, CrewAI, Codex, and A2A — mix any frameworks in one swarm with race-condition-safe shared state.(Traffic light for agents)

AgentPay — x402 crypto data gateway on Stellar. 10 live pay-per-call tools: token prices, whale activity, gas tracker, DeFi TVL, Fear & Greed, Dune queries, token security. Agents pay USDC on Stellar. No API keys. Budget-aware sessions.

Free MCP/API that scores a planned spend and returns approve, ask_human, or block so agents don't burn money by mistake.

Enables collaboration across Claude, GPT, and Gemini through a unified MCP interface, with configurable execution policies for synthesizing or directly delivering worker outputs.

A lightweight Model Context Protocol (MCP) server that enables your LLM to capture screenshots of any specified URL and return only the access URL for the captured image. This tool simplifies the process of generating and sharing webpage snapshots, making it perfect for integrating visual capture ca

Enables a host AI agent to trigger a multi-agent debate, running N-rounds where agents critique each other's answers, then synthesizes a consensus recommendation with ranked options.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

Enables Claude Code to browse and import conversations from a user's claude.ai account, making mobile chat history available in the editor. Includes tools to list, read, and save web conversations locally.

Lets separate coding-agent sessions coordinate through a shared, role-addressed mailbox instead of a human relaying every message, over a single local SQLite file or a hosted server with many isolated channels. Messages can be sent as tracked obligations that stay open until one side resolves and the other confirms, alongside threads, full-text search, work statuses, and an append-only versioned pin system where protected changes require recorded agreement from every declared role.

Enables AI coding agents from any vendor to resume a task from the exact stopping point without model calls, re-reading old sessions, or re-exploring the code, by merging host hooks, agent checkpoints, and Git deltas into one compact brief. It also guards credits outside the model with a prompt clarity gate, a loop guard, and configurable token profiles.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables Claude Code and other MCP clients to obtain fast, low-latency snap decisions — tool choice, option selection, and abstention when confidence is low — from a pluggable local decision engine such as Laya, Von, an Ollama chat model, or a custom provider. Engines can be swapped without changing the stable tools the client sees, with validation, per-attempt timeouts, confidence thresholds, and fallback chains handled by the server.

Enables AI agent hosts to exchange durable, local sender/receiver messages through a SQLite mailbox exposed as MCP tools (connect, send, receive, reply, ack, status, disconnect), so a coordinator can dispatch commands and an executor can return results without model polling while idle. A configured host wake adapter is still required to turn an incoming event into an Agent turn.

Discover which MCP servers can interact with real-world entities like restaurants, hotels, and salons by querying the Dock AI registry using domain names.

Swarm intelligence for AI agents, enabling collective decision-making through weighted consensus voting.

A multi-user AI group chat server via MCP that lets multiple users' AI agents join a shared discussion room to debate topics and reach convergence.

Provides AI-aware failover for Mihomo proxy on macOS by validating real OpenAI paths and switching proxy groups after verified hard failures. It offers a local stdio MCP server for diagnostics, status, and safe management of the AI proxy group.

Enables AI agents to execute multi-step Standard Operating Procedures step by step, with enforcement of completion at each step, making LLM behavior predictable and auditable.

A lightweight Model Context Protocol (MCP) orchestrator designed for efficiency at scale. It features TOON compression (reducing token usage by 30-90%) and Lazy Loading, making it the ideal solution for complex, multi-tool agentic workflows.

Enables enhanced decision-making through hierarchical LLM analysis, using three specialized critique agents (positive, neutral, negative) that analyze proposals in parallel and synthesize them into comprehensive, actionable insights. Helps overcome single-model biases by providing multi-perspective evaluation of complex ideas and proposals.

Enables browser automation for coding agents via MCP, allowing them to open pages, search, extract data, click, type, and complete multi-step tasks with fast single-round-trip decisions.

Enables Claude to orchestrate tasks across 27 AI providers, run multi-agent plans, and conduct multi-model councils for decision-making.

A dual-mode MCP server and CLI agent for AI-powered tasks including weather, news, file management, web scraping, and data processing via LangChain.

Token-saving MCP proxy. Hides your MCP servers' tool lists behind a search tool and shrinks large tool results (GitHub, Playwright, logs, test output), keeping the full result available on request. One-command setup for Claude Code, Codex, Claude Desktop and Cursor.

Enables any AI agent to connect to any OpenAI-compatible LLM provider through a unified MCP interface, with automatic failover, caching, cost tracking, and multi-model consensus.