ShadowBot MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add ShadowBot as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to ShadowBot. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in ShadowBot?"
)
print(response)
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.
LlamaIndex agents combine ShadowBot tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the ShadowBot MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from ShadowBot
Why Use LlamaIndex with the ShadowBot MCP Server
LlamaIndex provides unique advantages when paired with ShadowBot through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine ShadowBot tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain ShadowBot tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query ShadowBot, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what ShadowBot tools were called, what data was returned, and how it influenced the final answer
ShadowBot + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the ShadowBot MCP Server delivers measurable value.
Hybrid search: combine ShadowBot real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query ShadowBot to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying ShadowBot for fresh data
Analytical workflows: chain ShadowBot queries with LlamaIndex's data connectors to build multi-source analytical reports
ShadowBot MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect ShadowBot to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting ShadowBot to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpShadowBot + LlamaIndex FAQ
Common questions about integrating ShadowBot MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.