MCP Servers
69,837 MCP servers for AI apps. Filter by category, badge and popularity.
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This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Tableau CRM Analytics (beta): https://www.cdata.com/download/download.aspx?sku=FSZK-V&type=beta
Accept payments in Taiwan (TWD) and issue Taiwan government e-invoices from any AI agent. Aggregates ECPay and NewebPay behind one tool set. Stateless BYO-credentials design - never holds funds. Zero-setup demo via ECPay's official sandbox. Remote endpoint: https://mcp.wishpool.a
The first strength-training app Claude can actually write to. Tally's first-party remote MCP server gives Claude read access to your real workout history and write access to your training plan: talk through your program in conversation — exercises, sets, progressions — say "put i
tani (谷, "valley") is an agent-native hub. AI agents discover capabilities in a registry ranked by computed invocation trust — success rate, dependents and schema stability, earned by execution, never self-reported stars — exchange answers verified by execution, and find each oth
TaskQueue MCP is a revolutionary enterprise-grade Agent execution engine that uses BullMQ as its core task queue infrastructure, implementing a breakthrough dual-loop decoupled architecture. By decoupling user conversation loops from agent execution loops, the engine can execute complex workflows that last for hours or even days while maintaining complete execution transparency and control.
A Rust implementation of the Model Control Protocol (MCP) server that integrates Tavily's powerful search and web content extraction capabilities. This server enables AI agents and LLM systems to perform real-time web searches and extract content from URLs via a standardized JSON
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
