Tencent 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 Tencent 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 Tencent Docs. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Tencent 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 Tencent Docs MCP Server
Empower your AI agent to orchestrate your collaborative production with Tencent Docs, the premier office workspace for real-time collaboration. By connecting Tencent Docs to your agent, you transform complex file operations and spreadsheet management into a natural conversation. Your agent can instantly list your documents, create new files, retrieve spreadsheet data, and even monitor collaborators without you ever needing to navigate the web interface. Whether you are managing team reports or complex financial models, your agent acts as a real-time productivity assistant, keeping your workspace organized and your data accessible.
LlamaIndex agents combine Tencent 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
- File Orchestration — List all accessible documents, sheets, and slides across your Tencent Docs account.
- Spreadsheet Control — Retrieve and update values in specific ranges within your sheets with ease.
- Content Access — Retrieve the full text content of your documents for analysis and summarization.
- Collaboration Monitoring — List file collaborators and manage access insights for your team.
- Organization Overview — Access member lists to ensure effective coordination within your organization.
The Tencent 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 Tencent Docs to LlamaIndex via MCP
Follow these steps to integrate the Tencent 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 Tencent Docs
Why Use LlamaIndex with the Tencent Docs MCP Server
LlamaIndex provides unique advantages when paired with Tencent Docs through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Tencent Docs tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Tencent Docs tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Tencent Docs, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Tencent Docs tools were called, what data was returned, and how it influenced the final answer
Tencent Docs + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Tencent Docs MCP Server delivers measurable value.
Hybrid search: combine Tencent Docs real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Tencent 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 Tencent Docs for fresh data
Analytical workflows: chain Tencent Docs queries with LlamaIndex's data connectors to build multi-source analytical reports
Tencent Docs MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Tencent Docs to LlamaIndex via MCP:
create_file
Create a new document
delete_file
Delete a document
get_doc_content
Get document content
get_file_info
Get file metadata
get_org_members
List organization members
get_sheet_data
Read spreadsheet data
list_collaborators
List file collaborators
list_files
List all Tencent Docs files
list_folders
List all folders
update_sheet_data
Update spreadsheet data
Example Prompts for Tencent Docs in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Tencent Docs immediately.
"List all my documents on Tencent Docs."
"Read the values from 'Inventory!A1:B10' in spreadsheet 'doc-8821'."
"Create a new document titled 'Project Kickoff Notes'."
Troubleshooting Tencent Docs MCP Server with LlamaIndex
Common issues when connecting Tencent Docs to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTencent Docs + LlamaIndex FAQ
Common questions about integrating Tencent 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 Tencent 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 Tencent Docs to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.