Can I send a phone call with specific instructions using the agent?

Yes! Use the `send_call` action with the target phone number and a 'task' string describing exactly what the AI should say and do during the call.

How do I retrieve the transcript of a completed call?

Simply ask the agent to `get_transcript` and provide the Call ID. It will retrieve the full conversation log from the Bland AI engine.

Can I list all available voices before starting a call?

Yes. Use the `list_voices` tool to see all AI voices available in your Bland AI account, including their names and unique IDs.

Bland AI MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Bland AI
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 Bland AI through the 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({
        "bland-ai-1": {
            "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 Bland AI, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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 Bland AI MCP Server

Connect your Bland AI account to any AI agent and orchestrate your automated phone call workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Bland AI through native MCP adapters. Connect 10 tools via the 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

Outbound Automation — Send AI-powered phone calls with custom tasks and specific voices.
Call Monitoring — List recent calls and retrieve detailed metadata, including transcripts and analysis.
Agent Management — Access and manage your AI 'personas' (agents) used for different call scenarios.
Pathway Coordination — Retrieve and utilize complex conversation pathways for branching logic during calls.
Voice Discovery — List all available AI voices to find the perfect fit for your brand.
Operational Control — Stop active or scheduled calls instantly if needed.

The Bland AI 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 Bland AI to LangChain via MCP

Follow these steps to integrate the Bland AI 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 Bland AI via MCP

Why Use LangChain with the Bland AI MCP Server

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

The largest ecosystem of integrations, chains, and agents — combine Bland AI 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 Bland AI queries for multi-turn workflows

Bland AI + LangChain Use Cases

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

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

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

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

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

Bland AI MCP Tools for LangChain (10)

These 10 tools become available when you connect Bland AI to LangChain via MCP:

get_agent

Get details of a specific AI agent

get_call

Get details and metadata of a call

get_pathway

Get details of a specific pathway

get_transcript

Retrieve the transcript of a completed call

list_agents

List all AI agents

list_calls

List recent AI calls

list_pathways

List all conversation pathways

list_voices

List available AI voices

send_call

Send an AI phone call

stop_call

Stop an active or scheduled call

Example Prompts for Bland AI in LangChain

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

"Call +15550199 and ask if they are still interested in our pricing plan."

"List all AI agents in my account."

"Show the transcript for call call_998877."

Troubleshooting Bland AI MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Bland AI + LangChain FAQ

Common questions about integrating Bland AI 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.