TED EU MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add TED EU as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to TED EU. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in TED EU?"
)
print(response)
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.
LlamaIndex agents combine TED EU tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the TED EU MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 6 tools from TED EU
Why Use LlamaIndex with the TED EU MCP Server
LlamaIndex provides unique advantages when paired with TED EU through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine TED EU tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain TED EU tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query TED EU, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what TED EU tools were called, what data was returned, and how it influenced the final answer
TED EU + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the TED EU MCP Server delivers measurable value.
Hybrid search: combine TED EU real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query TED EU to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying TED EU for fresh data
Analytical workflows: chain TED EU queries with LlamaIndex's data connectors to build multi-source analytical reports
TED EU MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect TED EU to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting TED EU to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTED EU + LlamaIndex FAQ
Common questions about integrating TED EU MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.