YingDao RPA MCP Server

YingDao RPA MCP Server – Bridging AI Assistants with Robotic Process Automation

The YingDao RPA MCP Server addresses a common pain point for developers building intelligent agents: how to let an AI assistant orchestrate real‑world tasks that require interacting with desktop applications, filesystems, or enterprise RPA platforms. By exposing a Model Context Protocol (MCP) interface, the server lets AI agents invoke RPA workflows as first‑class tools, turning a conversational model into an automated worker that can launch applications, upload documents, and monitor job progress—all through a unified API surface.

At its core, the server implements two operational modes. In Local Mode, it runs against a locally installed instance of YindDao RPA (ShadowBot), allowing developers to test automation scripts on their own machine. In Open API Mode, it connects to the cloud‑hosted RPA service, enabling production workloads and enterprise authentication. The MCP server translates standard MCP calls into the underlying RPA commands, handling authentication tokens, file uploads, and job lifecycle events transparently.

Key capabilities include:

• Application discovery: and let the AI list available RPA applications and their configurable parameters, enabling dynamic selection of workflows.
• Execution control: (local) or (cloud) launches a chosen RPA job, while reports status and results.
• File handling: In cloud mode, streams documents directly to the RPA platform so that agents can provide inputs such as PDFs or spreadsheets.
• Client inventory: exposes the pool of RPA robot clients, useful for load balancing or diagnostics.

These features make the server invaluable in scenarios where an AI assistant must move beyond text generation. For example, a customer‑service bot can automatically open a ticketing application, fill out forms, and submit tickets; a data‑entry agent can pull documents from an email inbox, upload them to the RPA platform, and retrieve processed results—all within a single conversational flow. By integrating with popular MCP hosts like Claude Desktop or Cursor, developers can extend their AI workflows without writing custom connectors for each RPA system.

The server’s design prioritizes flexibility and ease of integration. It supports both SSE (Server‑Sent Events) for real‑time streaming responses and a lightweight Stdio mode for local development. This duality allows teams to choose the deployment style that best fits their infrastructure—whether running a simple local daemon or exposing a scalable web endpoint. Additionally, the open‑source MIT license and straightforward environment configuration make it quick to adopt in both prototype and production environments.

In summary, the YingDao RPA MCP Server transforms an AI assistant into a full‑stack automation orchestrator. By bridging conversational models with robust RPA tooling, it unlocks new possibilities for building intelligent agents that can interact with the physical world, streamline repetitive tasks, and deliver tangible business value.