Linkup (AI Search & RAG) MCP Server for LangChain 2 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Linkup (AI Search & RAG) 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({
"linkup-ai-search-rag": {
"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 Linkup (AI Search & RAG), 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 Linkup (AI Search & RAG) MCP Server
Connect your Linkup account to any AI agent and take full control of real-time web intelligence and content retrieval for RAG pipelines through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Linkup (AI Search & RAG) through native MCP adapters. Connect 2 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.
What you can do
- Semantic Web Search — Execute context-rich queries that return high-relevancy results specifically optimized for Large Language Models directly from your agent
- Deep Content Retrieval — Extract clean, readable text from any web URL, stripping away noise and navigation to feed high-quality grounding data to your AI
- RAG-Ready Payloads — Retrieve structured search results including titles, snippets, and source URLs designed for seamless integration into vector stores
- Precision Extraction — Target specific URLs for content parsing, ensuring your agent has the exact technical context or documentation required for its task
- Real-time Intelligence — Access the latest facts and data from across the internet to ground your agent's answers in up-to-date reality
- Search Breadth — Switch between standard and deep search modes to balance between rapid fact-finding and comprehensive research across the web
The Linkup (AI Search & RAG) MCP Server exposes 2 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 Linkup (AI Search & RAG) to LangChain via MCP
Follow these steps to integrate the Linkup (AI Search & RAG) 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 2 tools from Linkup (AI Search & RAG) via MCP
Why Use LangChain with the Linkup (AI Search & RAG) MCP Server
LangChain provides unique advantages when paired with Linkup (AI Search & RAG) through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) queries for multi-turn workflows
Linkup (AI Search & RAG) + LangChain Use Cases
Practical scenarios where LangChain combined with the Linkup (AI Search & RAG) MCP Server delivers measurable value.
RAG with live data: combine Linkup (AI Search & RAG) tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Linkup (AI Search & RAG), synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Linkup (AI Search & RAG) tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Linkup (AI Search & RAG) tool call, measure latency, and optimize your agent's performance
Linkup (AI Search & RAG) MCP Tools for LangChain (2)
These 2 tools become available when you connect Linkup (AI Search & RAG) to LangChain via MCP:
fetch_url
Bypasses advanced bot protections executing complex SPA JavaScript loops automatically. Fetch and extract clean content from any specific URL using Linkup Platform
search_web
Choose "fast" mapping for basic factual requests and "deep" for thorough research limits. Perform a real-time web search extracting deep answers utilizing Linkup Platform
Example Prompts for Linkup (AI Search & RAG) in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Linkup (AI Search & RAG) immediately.
"Search for the latest NVIDIA earnings report summary"
"Extract the technical specifications from this documentation URL: [url]"
"Deep search for 'AI agent security best practices 2024'"
Troubleshooting Linkup (AI Search & RAG) MCP Server with LangChain
Common issues when connecting Linkup (AI Search & RAG) to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersLinkup (AI Search & RAG) + LangChain FAQ
Common questions about integrating Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) to LangChain
Get your token, paste the configuration, and start using 2 tools in under 2 minutes. No API key management needed.