SERPHouse MCP Server for LangChain 11 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect SERPHouse through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
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({
"serphouse": {
"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 SERPHouse, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 SERPHouse MCP Server
Equip your AI assistant with the ultimate crawler module engineered for unbridled search engine access. The SERPHouse MCP integration overcomes the constraints of offline AI knowledge by granting direct, proxy-rotated querying power over Google and Bing endpoints. Seamlessly transform your agent into a high-performance web discovery engine without triggering Captcha blocks.
LangChain's ecosystem of 500+ components combines seamlessly with SERPHouse through native MCP adapters. Connect 11 tools via 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.
The SERPHouse MCP Server exposes 11 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 SERPHouse to LangChain via MCP
Follow these steps to integrate the SERPHouse 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 11 tools from SERPHouse via MCP
Why Use LangChain with the SERPHouse MCP Server
LangChain provides unique advantages when paired with SERPHouse through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine SERPHouse 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 SERPHouse queries for multi-turn workflows
SERPHouse + LangChain Use Cases
Practical scenarios where LangChain combined with the SERPHouse MCP Server delivers measurable value.
RAG with live data: combine SERPHouse tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query SERPHouse, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain SERPHouse tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every SERPHouse tool call, measure latency, and optimize your agent's performance
SERPHouse MCP Tools for LangChain (11)
These 11 tools become available when you connect SERPHouse to LangChain via MCP:
bing_images
Searches for images on Bing
bing_news
Searches for news on Bing
bing_search
Performs a search on Bing
get_account_info
Retrieves SERPHouse account information
google_images
Searches for images on Google
google_news
Searches for news on Google
google_scholar
Searches for scholarly articles on Google Scholar
google_search
Supports advanced parameters like "location" and "lang". Performs a search on Google
google_shopping
Searches for products on Google Shopping
google_videos
Searches for videos on Google
list_locations
Lists supported locations for SERP queries
Example Prompts for SERPHouse in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with SERPHouse immediately.
"Run a targeted Google Scholar query aimed at finding recent papers on 'quantum consciousness theory' focusing on latest available years."
"Search Bing News locally from a generic 'United Kingdom' location tag to see the latest headlines on economic metrics."
Troubleshooting SERPHouse MCP Server with LangChain
Common issues when connecting SERPHouse to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersSERPHouse + LangChain FAQ
Common questions about integrating SERPHouse MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect SERPHouse 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 SERPHouse to LangChain
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.