FlowUs MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect FlowUs through 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({
"flowus": {
"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 FlowUs, 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 FlowUs MCP Server
Empower your AI agent to orchestrate your knowledge base with FlowUs, the versatile collaboration platform for modern individuals and teams. By connecting FlowUs to your agent, you transform complex page organization and database management into a natural conversation. Your agent can instantly list your pages, retrieve block-level content, manage multi-dimensional databases, and even create new entries without you needing to navigate the complex web interface. Whether you are managing personal notes, project documentation, or shared team databases, your agent acts as a real-time knowledge assistant, keeping your workspace organized and your information accessible.
LangChain's ecosystem of 500+ components combines seamlessly with FlowUs through native MCP adapters. Connect 10 tools via 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
- Page Orchestration — List all accessible pages and retrieve detailed metadata about your workspace structure.
- Block Management — Browse content blocks within pages to access text and media information instantly.
- Database Control — Manage multi-dimensional tables (databases) with full support for querying and creating new rows.
- Workspace Organization — Create and update pages to maintain a clean and structured knowledge base.
- Team Coordination — Access workspace user lists to manage participation and collaboration effectively.
The FlowUs 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 FlowUs to LangChain via MCP
Follow these steps to integrate the FlowUs 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 FlowUs via MCP
Why Use LangChain with the FlowUs MCP Server
LangChain provides unique advantages when paired with FlowUs through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine FlowUs 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 FlowUs queries for multi-turn workflows
FlowUs + LangChain Use Cases
Practical scenarios where LangChain combined with the FlowUs MCP Server delivers measurable value.
RAG with live data: combine FlowUs tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query FlowUs, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain FlowUs tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every FlowUs tool call, measure latency, and optimize your agent's performance
FlowUs MCP Tools for LangChain (10)
These 10 tools become available when you connect FlowUs to LangChain via MCP:
create_database_row
Add row to database
create_page
Create a new FlowUs page
get_database
Get database schema
get_page
Get page details
list_blocks
) within a specific page. List page blocks
list_databases
List all FlowUs databases
list_pages
List all FlowUs pages
list_users
List workspace users
query_database
Query database rows
update_page
Update an existing page
Example Prompts for FlowUs in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with FlowUs immediately.
"List all pages in my FlowUs workspace."
"Query the 'Product Backlog' database for items with 'High' priority."
"Add a new row to the 'User Feedback' database with Name='Renato' and Feedback='Love the AI integration!'."
Troubleshooting FlowUs MCP Server with LangChain
Common issues when connecting FlowUs to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersFlowUs + LangChain FAQ
Common questions about integrating FlowUs 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 FlowUs 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 FlowUs to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.