Sendbird MCP Server for LangChainGive LangChain instant access to 18 tools to Ban User, Block User, Create Bot, and more

Name: Sendbird
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect Sendbird 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 for LangChain

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The Sendbird MCP Server for LangChain is a standout in the Communication Messaging category — giving your AI agent 18 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

Claude

ChatGPT

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Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

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

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

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 Sendbird MCP Server

Connect your Sendbird application to any AI agent and take full control of your chat ecosystem through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Sendbird through native MCP adapters. Connect 18 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

User Management — Create new users, list existing ones, and manage profiles or access tokens for your chat application.
Channel Orchestration — Create and manage Open Channels for massive public scale or Group Channels for private, distinct conversations.
Moderation & Safety — Maintain community standards by blocking, muting, or banning users, and freezing channels during incidents.
Automation & Bots — Create and manage bots to send automated messages and interact with users programmatically.
Channel Lifecycle — Update channel metadata, join or leave group chats, and invite new members seamlessly.

The Sendbird MCP Server exposes 18 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 18 Sendbird tools available for LangChain

When LangChain connects to Sendbird through Vinkius, your AI agent gets direct access to every tool listed below — spanning in-app-chat, messaging-api, user-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

ban

Ban user on Sendbird

Ban a user from a channel

block

Block user on Sendbird

Block a user

create

Create bot on Sendbird

Create a bot

create

Create group channel on Sendbird

Create a group channel

create

Create open channel on Sendbird

Create an open channel

create

Create user on Sendbird

Create a new Sendbird user

delete

Delete open channel on Sendbird

Delete an open channel

freeze

Freeze channel on Sendbird

Freeze a channel

get

Get open channel on Sendbird

Get an open channel by URL

invite

Invite group channel on Sendbird

Invite users to a group channel

join

Join group channel on Sendbird

Join a group channel

leave

Leave group channel on Sendbird

Leave a group channel

list

List open channels on Sendbird

List open channels

list

List users on Sendbird

List Sendbird users

mute

Mute user on Sendbird

Mute a user in a channel

send

Send bot message on Sendbird

Send a message via bot

send

Send message on Sendbird

Send a message to a channel

update

Update open channel on Sendbird

Update an open channel

Connect Sendbird to LangChain via MCP

Follow these steps to wire Sendbird into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 18 tools from Sendbird via MCP

Why Use LangChain with the Sendbird MCP Server

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

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

Sendbird + LangChain Use Cases

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

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

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

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

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

Example Prompts for Sendbird in LangChain

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

"List the first 10 users in our Sendbird application."

"Create a new open channel called 'Global-Lounge' for our community."

"Freeze the channel at URL 'sendbird_open_channel_123' to stop all messaging."

Troubleshooting Sendbird MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Sendbird + LangChain FAQ

Common questions about integrating Sendbird 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.