How do I get my Common Room API token?

Go to **Settings > API Tokens** in Common Room and generate a new token. Copy it and paste it into the field below.

What is a segment in Common Room?

A segment is a group of contacts or organizations defined by specific criteria or manually curated. They help you target and analyze subsets of your community.

Can I track custom activities?

Yes, but you first need to set up an API Signal in Common Room to receive custom activity data. Once configured, the agent can query those activities.

Common Room MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Common Room
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Common Room 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({
        "common-room": {
            "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 Common Room, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Common Room MCP Server

Connect your AI assistant to Common Room, the intelligent community growth platform that helps organizations find and build relationships with community members.

LangChain's ecosystem of 500+ components combines seamlessly with Common Room 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

Contact Search — Find community members by email, name, or external identity across connected platforms.
Segment Management — List all segments, view member counts, and add or remove contacts from specific cohorts.
Activity Tracking — Retrieve activity feeds to understand engagement patterns and identify key contributors.

The Common Room 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 Common Room to LangChain via MCP

Follow these steps to integrate the Common Room 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 Common Room via MCP

Why Use LangChain with the Common Room MCP Server

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

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

Common Room + LangChain Use Cases

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

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

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

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

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

Common Room MCP Tools for LangChain (10)

These 10 tools become available when you connect Common Room to LangChain via MCP:

add_contact_to_segment

Manually add a contact to a specific segment

get_contact_by_email

Retrieve detailed information about a member by their email

get_contact_tags

Get tags associated with a specific member

get_organization_details

Retrieve details of a specific organization

get_segment_status

Retrieve status and member count for a specific segment

list_activity_types

Retrieve a list of supported activity types in Common Room

list_segment_members

List contacts that belong to a specific segment

list_segments

Retrieve a list of all segments in Common Room

search_contacts

Search for contacts/members in your Common Room

search_organizations

Search for organizations in Common Room

Example Prompts for Common Room in LangChain

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

"Search for the member with email 'dev@example.com'."

"Show me all segments and their member counts."

"Add 'Alex Chen' to the 'Enterprise Leads' segment."

Troubleshooting Common Room MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Common Room + LangChain FAQ

Common questions about integrating Common Room 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.