ShadowBot MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect ShadowBot through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MultiServerMCPClient({
"shadowbot": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using ShadowBot, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About ShadowBot MCP Server
Connect your AI agents to ShadowBot (影刀RPA), the leading Robotic Process Automation (RPA) platform for high-performance browser and desktop automation. This MCP provides 10 tools to manage automation robots, orchestrate execution tasks, and monitor the health of your digital workforce programmatically.
LangChain's ecosystem of 500+ components combines seamlessly with ShadowBot through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Robot Orchestration — List and inspect available automation robots and their current operational status
- Task Execution — Trigger specific automation tasks and handle job lifecycle management from start to finish
- Performance Monitoring — Retrieve granular execution logs and track robot throughput and success rates
- Credential Handling — Monitor and manage robotic account assignments and access tokens for secure automation
- Global Management — Access organizational project structures and list active automation workflows directly from your agent
The ShadowBot MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect ShadowBot to LangChain via MCP
Follow these steps to integrate the ShadowBot MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from ShadowBot via MCP
Why Use LangChain with the ShadowBot MCP Server
LangChain provides unique advantages when paired with ShadowBot through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine ShadowBot MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across ShadowBot queries for multi-turn workflows
ShadowBot + LangChain Use Cases
Practical scenarios where LangChain combined with the ShadowBot MCP Server delivers measurable value.
RAG with live data: combine ShadowBot tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query ShadowBot, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain ShadowBot tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every ShadowBot tool call, measure latency, and optimize your agent's performance
ShadowBot MCP Tools for LangChain (10)
These 10 tools become available when you connect ShadowBot to LangChain via MCP:
get_robot_details
Get detailed information for a specific robot
get_task_details
Retrieve the status and results of a ShadowBot task
list_apps
List all RPA applications in your ShadowBot account
list_department_members
List members in a specific department
list_departments
Retrieve the organizational department list
list_online_robots
List currently online robots
list_robots
List all robots associated with the account
list_task_logs
Retrieve logs for a specific task
start_task
Remote trigger a ShadowBot RPA application
stop_task
Stop a running ShadowBot task
Example Prompts for ShadowBot in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with ShadowBot immediately.
"List all automation robots in my ShadowBot account and show their status."
"Start task 'process_invoices' on robot ID 'bot_rpa_777'."
"Get the execution logs for Job ID 'job_12345'."
Troubleshooting ShadowBot MCP Server with LangChain
Common issues when connecting ShadowBot to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersShadowBot + LangChain FAQ
Common questions about integrating ShadowBot MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect ShadowBot with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect ShadowBot to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.