MessageBird MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add MessageBird as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 MessageBird. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in MessageBird?"
)
print(response)
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 MessageBird MCP Server
Empower your AI agent to orchestrate your entire global communication strategy with MessageBird, the leading omnichannel platform. By connecting MessageBird to your agent, you transform complex messaging workflows into a natural conversation. Your agent can instantly send SMS to multiple recipients, audit your contact database, and check your real-time account balance without you ever touching a dashboard. Whether you are providing verification codes or managing marketing broadcasts, your agent acts as a real-time communication coordinator, ensuring your messages are delivered and your audience data is organized.
LlamaIndex agents combine MessageBird tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Messaging Intelligence — Send SMS messages to global recipients and retrieve detailed delivery status and history.
- Contact Auditing — List and retrieve detailed metadata for your global contact database and groups.
- Financial Oversight — Check your real-time account balance to maintain strict organizational control over your costs.
- Channel Management — List configured communication channels to ensure your omnichannel strategy is active.
- Network Intelligence — List HLR (Home Location Register) requests to verify number validity and network status.
The MessageBird MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex 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 MessageBird to LlamaIndex via MCP
Follow these steps to integrate the MessageBird MCP Server with LlamaIndex.
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 10 tools from MessageBird
Why Use LlamaIndex with the MessageBird MCP Server
LlamaIndex provides unique advantages when paired with MessageBird through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine MessageBird tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain MessageBird tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query MessageBird, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what MessageBird tools were called, what data was returned, and how it influenced the final answer
MessageBird + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the MessageBird MCP Server delivers measurable value.
Hybrid search: combine MessageBird real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query MessageBird 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 MessageBird for fresh data
Analytical workflows: chain MessageBird queries with LlamaIndex's data connectors to build multi-source analytical reports
MessageBird MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect MessageBird to LlamaIndex via MCP:
get_balance
Get current MessageBird account balance
get_contact
Get details for a specific contact
get_group
Get details for a specific group
get_message
Get details for a specific message
list_channels
List configured channels
list_contacts
List MessageBird contacts
list_groups
List contact groups
list_hlr
List HLR (Network Lookup) requests
list_messages
List recent SMS messages
send_sms
Send an SMS message
Example Prompts for MessageBird in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with MessageBird immediately.
"Check my MessageBird account balance."
"List the last 5 SMS messages sent from my account."
"Send SMS 'Your discount code is VINKIUS20' to +15550123."
Troubleshooting MessageBird MCP Server with LlamaIndex
Common issues when connecting MessageBird to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMessageBird + LlamaIndex FAQ
Common questions about integrating MessageBird MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect MessageBird 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 MessageBird to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.