How to Use the isvat MCP in LlamaIndex
Audit and index European VAT numbers inside your LlamaIndex RAG pipelines with this MCP Server.
Works with every AI agent you already use
…and any MCP-compatible client
Connect isvat MCP to LlamaIndex
Create your Vinkius account to connect isvat to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Inject Live Tax Registry Data Into Vectors
`validate_eu_vat` pulls live tax status and company registry details directly into your LlamaIndex knowledge indexes. Your agent queries the official EU databases, confirms validation status, and immediately saves the structured metadata into your vector store. This prevents your RAG system from relying on stale, hallucinated tax records. When a user asks about a vendor's tax status, the agent searches the index of recently verified VAT numbers, pulling up-to-date compliance records without hitting the external API every single time.
Index Bulk Validations from Unstructured Files
`validate_multiple_vat` lets your LlamaIndex agent run batch tax audits on raw documents or unstructured tables. Your agent parses PDF invoices, extracts all European tax IDs, and verifies them concurrently in a single operation. The verified results are indexed as document nodes with precise metadata. You can then run semantic searches over your vendor list to quickly identify which entities have active, inactive, or completely invalid VAT registrations.
Index API Health States in your LlamaIndex App
`check_api_status` checks the availability of the VIES registry before your LlamaIndex agent invokes the MCP Server. Because European tax databases frequently go offline, this check stops your ingestion pipelines from failing due to external downtime. Your agent can write the current API status to your index logs. This creates an audit trail that explains why certain tax numbers couldn't be verified at a specific moment, keeping your database clean and your RAG outputs accurate.
Set up isvat MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports. - 3
Convert to LlamaIndex tools
Call
mcp_tool_spec.to_tool_list_async()to convert all isvat MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
# Connect to the MCP
mcp_client = BasicMCPClient(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)
# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()
# Create and run the agent
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt="You have access to isvat tools.",
)
response = await agent.run("List recent isvat data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by isvat. 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.
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Common questions about isvat MCP in LlamaIndex
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