Sendbird MCP Server for LlamaIndexGive LlamaIndex 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

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Sendbird 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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The Sendbird MCP Server for LlamaIndex 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

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python

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 Sendbird. "
            "You have 18 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Sendbird?"
    )
    print(response)

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 Sendbird MCP Server

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

LlamaIndex agents combine Sendbird tool responses with indexed documents for comprehensive, grounded answers. Connect 18 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

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 LlamaIndex 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 LlamaIndex

When LlamaIndex 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 LlamaIndex via MCP

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

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 18 tools from Sendbird

Why Use LlamaIndex with the Sendbird MCP Server

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

Data-first architecture: LlamaIndex agents combine Sendbird tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Sendbird tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Sendbird, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Sendbird tools were called, what data was returned, and how it influenced the final answer

Sendbird + LlamaIndex Use Cases

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

Hybrid search: combine Sendbird real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Sendbird 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 Sendbird for fresh data

Analytical workflows: chain Sendbird queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Sendbird in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

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

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Sendbird + LlamaIndex FAQ

Common questions about integrating Sendbird MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Sendbird tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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