How to Use the Bird (MessageBird) MCP in LangChain

Q: Can I trace Bird (MessageBird) tool calls using LangSmith?

Yes, every tool invocation like listconversations or getcall shows up in your LangSmith dashboard. You can inspect the exact JSON payloads, latency, and token usage for each communication step.

Run multi-step communication chains in LangChain with direct access to your Bird (MessageBird) contacts, messages, and calls.

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Connect Bird (MessageBird) MCP to LangChain

Create your Vinkius account to connect Bird (MessageBird) to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Bird (MessageBird) with LangChain

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Chain Bird (MessageBird) message tools into LangChain agents

The `send_message` tool lets your LangChain agent send SMS or WhatsApp messages directly inside an active run via our MCP Server. Your agent reads incoming data, selects the correct channel ID, and writes the message payload without manual code. By feeding the output of one step into the next, your agent can lookup a profile using `get_contact` and immediately use those details to route a message. LangSmith traces every step of this execution so you see the exact payload passed to the API.

Build self-correcting voice and conversation loops

The `list_calls` tool pulls call records straight into your LangChain agent's reasoning loop. Your agent checks active call statuses, identifies dropped connections, and triggers follow-up actions based on real-time data. If a call fails, the agent uses `get_conversation` to check if the user is active on another channel. This lets your agent switch from voice to text dynamically without you writing custom routing logic for every edge case.

Keep contact profiles synchronized automatically

The `update_contact` tool updates your Bird workspace metadata directly from your LangChain execution paths. You pass a JSON string with the updated fields, and the agent writes the changes to the user's profile instantly. When a customer updates their information in a chat, the agent verifies the new details and runs `create_contact` to register new communication identifiers. This keeps your central contact directory updated without manual database exports.

Setup guide

Set up Bird (MessageBird) MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Bird (MessageBird) tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "bird-messagebird-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Bird (MessageBird) transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bird. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Bird (MessageBird) MCP in LangChain

Your LangChain agent evaluates the recipient's profile and uses `send_message` with the correct channel ID. The agent determines whether to route via SMS or WhatsApp based on the contact data it retrieves during the chain execution.

Yes, every tool invocation like `list_conversations` or `get_call` shows up in your LangSmith dashboard. You can inspect the exact JSON payloads, latency, and token usage for each communication step.

Initialize the MCP client with MultiServerMCPClient and use the session context to maintain state across multiple turns. This ensures your agent remembers the active conversation ID returned by `list_conversations` during the run.

You must format the identifiers as a JSON string when calling `create_contact` within your agent. For example, pass a string like `[{"key":"phone","value":"+123"}]` so the server can register the contact correctly.

All contact profiles, call logs, and message contents are processed inside ephemeral V8 isolates on Vinkius. No customer data is stored on our servers, and your API tokens are encrypted at rest.

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