TED EU MCP Server for LangChain 6 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect TED EU through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
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({
"ted-eu": {
"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 TED EU, 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 TED EU MCP Server
Connect TED (Tenders Electronic Daily) to any AI agent and search EU public procurement opportunities through natural conversation instead of navigating complex procurement portals.
LangChain's ecosystem of 500+ components combines seamlessly with TED EU through native MCP adapters. Connect 6 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
- Full-Text Search — Search across all TED procurement notices using keywords like "software development" or "medical equipment"
- Country Filtering — Find active tenders from any of the 27 EU member states using ISO country codes
- CPV Classification — Search by Common Procurement Vocabulary codes to target specific industry sectors
- Value Range Search — Filter tenders by contract value in EUR to match your company size and capacity
- Recent Opportunities — Monitor newly published tenders from the last 7 days to stay ahead of deadlines
- Notice Details — Retrieve full procurement details including lots, award criteria, timelines, and contracting authority contacts
The TED EU MCP Server exposes 6 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 TED EU to LangChain via MCP
Follow these steps to integrate the TED EU 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 6 tools from TED EU via MCP
Why Use LangChain with the TED EU MCP Server
LangChain provides unique advantages when paired with TED EU through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine TED EU 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 TED EU queries for multi-turn workflows
TED EU + LangChain Use Cases
Practical scenarios where LangChain combined with the TED EU MCP Server delivers measurable value.
RAG with live data: combine TED EU tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query TED EU, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain TED EU tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every TED EU tool call, measure latency, and optimize your agent's performance
TED EU MCP Tools for LangChain (6)
These 6 tools become available when you connect TED EU to LangChain via MCP:
get_tender
Includes description, lots, award criteria, timelines, and contracting authority contact. Get tender notice details
list_recent_tenders
Default is 7 days. Use to monitor new opportunities. List recently published tenders
search_by_country
Use ISO country codes: DE, FR, ES, IT, PT, NL, etc. Search tenders by country
search_by_cpv
CPV codes classify EU contracts by sector: 72000000 (IT), 45000000 (Construction), 33000000 (Medical). Search tenders by CPV code
search_by_value
Useful for finding contracts matching your company size. Search tenders by contract value
search_tenders
Returns title, country, value, deadline, and contracting authority. Covers all 27 EU member states. Search EU public tenders
Example Prompts for TED EU in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with TED EU immediately.
"Find recent tenders for software development in France."
"Show me construction tenders worth over 5 million euros."
"What new tenders were published this week?"
Troubleshooting TED EU MCP Server with LangChain
Common issues when connecting TED EU to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTED EU + LangChain FAQ
Common questions about integrating TED EU 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 TED EU 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 TED EU to LangChain
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.