Can I see who has booked a specific meeting room today?

Yes! Use the `list_space_bookings` tool with today's date range. The agent will return all bookings, allowing you to see which members have reserved specific rooms.

How do I check the status of a member's last invoice?

Use the `list_cobot_invoices` tool. Your agent will fetch all invoices, and you can filter for a specific member's name or ID to see if their last payment was successful.

Where do I find my Cobot Access Token and Subdomain?

The **Subdomain** is the first part of your Cobot URL (e.g., `myspace` in `myspace.cobot.me`). You can generate an **Access Token** via the Cobot developer portal or by creating an application in your account settings.

Cobot MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Cobot
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Cobot through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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({
        "cobot": {
            "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 Cobot, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Cobot MCP Server

Connect your Cobot account to any AI agent and take full control of your coworking space management through natural conversation. Streamline how you manage members, resources, and billing natively.

LangChain's ecosystem of 500+ components combines seamlessly with Cobot through native MCP adapters. Connect 8 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

Membership Oversight — List and retrieve details for all active memberships including their names and plan details natively
Booking Intelligence — Access and monitor resource bookings within specific date ranges flawlessly
Resource Management — List all bookable resources like desks and meeting rooms flawlessly
Booking Lifecycle — Create new bookings for resources directly from your chat interface securely
Invoicing Logistics — List and review membership invoices and their payment status flawlessly
Space Visibility — Retrieve core information and metadata about your coworking space directly within your workspace

The Cobot MCP Server exposes 8 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 Cobot to LangChain via MCP

Follow these steps to integrate the Cobot 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 8 tools from Cobot via MCP

Why Use LangChain with the Cobot MCP Server

LangChain provides unique advantages when paired with Cobot through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Cobot 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 Cobot queries for multi-turn workflows

Cobot + LangChain Use Cases

Practical scenarios where LangChain combined with the Cobot MCP Server delivers measurable value.

RAG with live data: combine Cobot tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Cobot, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Cobot tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Cobot tool call, measure latency, and optimize your agent's performance

Cobot MCP Tools for LangChain (8)

These 8 tools become available when you connect Cobot to LangChain via MCP:

create_new_booking

Create a new booking for a resource

get_cobot_space_info

Retrieve core information and metadata about the coworking space

get_membership_details

Get detailed information for a specific membership

list_cobot_invoices

List all membership invoices and their payment status

list_cobot_memberships

List all active memberships in the coworking space

list_membership_plans

List all available membership plans in the space

list_space_bookings

List all resource bookings within a specific date range

list_space_resources

List all bookable resources (desks, rooms) in the space

Example Prompts for Cobot in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Cobot immediately.

"List all active memberships in my coworking space."

"Show me the bookings for 'Large Meeting Room' for this week."

"Are there any unpaid invoices from last month?"

Troubleshooting Cobot MCP Server with LangChain

Common issues when connecting Cobot to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Cobot + LangChain FAQ

Common questions about integrating Cobot MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use 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?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.