How to Use the Bing Search MCP in LangChain

Build multi-step reasoning chains in LangChain using live web data from the Bing Search MCP Server.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect Bing Search MCP to LangChain

Create your Vinkius account to connect Bing Search 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 Bing Search with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Bing Search results in LangChain

Feed `search_web` or `search_news` output directly into your next chain link. Your agent evaluates the data and decides whether to trigger another tool or finish the sequence. This workflow lets you build complex logic where one step depends on the previous result. You get full LangSmith tracing for every tool interaction.

Automate content discovery for LangChain

Use `get_trending_news` to pull fresh topics into your pipeline. Your agent processes these headlines to generate summaries or draft reports automatically. Everything happens in one script. Connect the MCP Server, define your chain, and watch the agent handle the heavy lifting.

Visual and local data in LangChain

Call `search_images` or `search_local` to inject specific media or location data into your prompt context. Your agent uses these details to provide grounded, location-aware answers. This keeps your application context updated without hardcoding any values. Just pipe the tool output into your prompt template.

Setup guide

Set up Bing Search 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 Bing Search 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({
    "bing-search-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 Bing Search 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 Bing Search. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Bing Search now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Bing Search MCP in LangChain

Yes. You pass the server tools directly to your agent configuration. The agent then decides when to invoke them during the chain execution.

Use LangSmith integration. It logs every input and output for your tools, letting you spot latency or bad data in real-time.

LangChain handles state management separately. You can use the client session to maintain context across multiple tool calls.

The chain catches the error. You can define fallback logic or retries within your code to keep the agent running.

We only process your search queries and the resulting web metadata. Your session data remains local and is never stored on our servers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript

Mastra AI sdk-typescript

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