Shimo Docs 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 Shimo Docs as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 Shimo Docs. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Shimo Docs?"
)
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 Shimo Docs MCP Server
Empower your AI agent to orchestrate your collaborative workflow with Shimo Docs, the leading professional office suite in China. By connecting Shimo Docs to your agent, you transform complex document management and team collaboration into a natural conversation. Your agent can instantly list your files, create new collaborative documents, import external content, and even export your work into multiple formats without you ever needing to navigate the web interface. Whether you are managing complex project documentation or financial spreadsheets, your agent acts as a real-time collaborative assistant, keeping your files organized and your team aligned.
LlamaIndex agents combine Shimo Docs tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through 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
- Document Orchestration — List all accessible documents, sheets, and presentations across your workspace.
- File Management — Create, retrieve, and delete files with full support for collaborative metadata.
- Import & Export — Seamlessly import external content and export Shimo documents into standard formats like docx and pdf.
- Folder Organization — Browse folder structures and manage file locations efficiently.
- Administrative Insights — List organization users and monitor audit logs for security and compliance.
The Shimo Docs 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 Shimo Docs to LlamaIndex via MCP
Follow these steps to integrate the Shimo Docs 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 Shimo Docs
Why Use LlamaIndex with the Shimo Docs MCP Server
LlamaIndex provides unique advantages when paired with Shimo Docs through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Shimo Docs tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Shimo Docs tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Shimo Docs, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Shimo Docs tools were called, what data was returned, and how it influenced the final answer
Shimo Docs + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Shimo Docs MCP Server delivers measurable value.
Hybrid search: combine Shimo Docs real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Shimo Docs 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 Shimo Docs for fresh data
Analytical workflows: chain Shimo Docs queries with LlamaIndex's data connectors to build multi-source analytical reports
Shimo Docs MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Shimo Docs to LlamaIndex via MCP:
create_file
Create a new Shimo file
export_file
Export a Shimo file
get_file
Get file details
get_folder_content
Get folder contents
get_org_info
Get organization details
import_file
Import a document into Shimo
list_audit_logs
List audit logs
list_files
List all Shimo files
list_folders
List all Shimo folders
list_users
List organization users
Example Prompts for Shimo Docs in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Shimo Docs immediately.
"List all my collaborative documents on Shimo."
"Create a new spreadsheet titled 'Q2 Expenses' in folder 'Finance'."
"Export the document 'Project Roadmap' to PDF."
Troubleshooting Shimo Docs MCP Server with LlamaIndex
Common issues when connecting Shimo Docs to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpShimo Docs + LlamaIndex FAQ
Common questions about integrating Shimo Docs 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 Shimo Docs 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 Shimo Docs to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.