How do I get started?

Subscribe, copy your active API Key (which you can generate inside **HiDeliver Portal → Security/Dev Settings**), and connect it. The integration expects standard raw API connections so you interact intuitively through words instead of intricate data schemas.

Can it query active subscriber details globally?

Yes! Direct your AI agent to query list nodes or fetch the comprehensive subscriber logs. The `list_subscribers` action aggregates arrays of real, valid accounts securely for your reporting needs in an instant.

What happens when I want to fetch metrics or fields for one target list?

Provide the exact List ID. The tool evaluates endpoint rules (`get_list`) and unpacks default configuration details (such as names, double-opt rules, and associated status) natively to the terminal.

Can my AI automatically create or append specific subscriber profiles?

Absolutely. Pass specific parameters, including the new email, name, and respective list ID. The system validates the JSON schema instantly with the `create_subscriber` pipeline effectively logging campaigns on the fly.

HiDeliver MCP Server for LlamaIndex 9 tools — connect in under 2 minutes

Name: HiDeliver
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 9 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add HiDeliver as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 HiDeliver. "
            "You have 9 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in HiDeliver?"
    )
    print(response)

asyncio.run(main())

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* 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 HiDeliver MCP Server

Connect your HiDeliver broadcasting account to an AI agent to execute bulk email campaigns directly through conversations.

LlamaIndex agents combine HiDeliver tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through 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

Client Lists — Fetch stored customer addresses and list segments immediately to verify delivery rules
Audience Management — Inspect or create subscriber leads straight from within conversational prompts
Campaign Insights — Pull real-time delivery performance lists and broadcast statistics without entering the application

The HiDeliver MCP Server exposes 9 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 HiDeliver to LlamaIndex via MCP

Follow these steps to integrate the HiDeliver 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 9 tools from HiDeliver

Why Use LlamaIndex with the HiDeliver MCP Server

LlamaIndex provides unique advantages when paired with HiDeliver through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine HiDeliver tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain HiDeliver tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query HiDeliver, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what HiDeliver tools were called, what data was returned, and how it influenced the final answer

HiDeliver + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the HiDeliver MCP Server delivers measurable value.

Hybrid search: combine HiDeliver real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query HiDeliver 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 HiDeliver for fresh data

Analytical workflows: chain HiDeliver queries with LlamaIndex's data connectors to build multi-source analytical reports

HiDeliver MCP Tools for LlamaIndex (9)

These 9 tools become available when you connect HiDeliver to LlamaIndex via MCP:

cancel_delivery

Cancel a mapped delivery trace

create_delivery

Log and schedule a fresh pickup delivery

get_account_balance

Evaluate remaining tokens or cash thresholds

get_delivery

Get parameters surrounding an explicit delivery

get_profile

Get HiDeliver authenticated account logic

get_transaction

Isolate a single API key transaction

list_deliveries

Retrieve active or listed delivery requests

list_transactions

Check global ledger events

update_delivery

Adjust active route parameters

Example Prompts for HiDeliver in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with HiDeliver immediately.

"Display all the actively loaded marketing lists right now."

"Fetch the underlying metadata and info associated with list ID 55102."

"Add the new email address 'lead@example.com' to list 55301."

Troubleshooting HiDeliver MCP Server with LlamaIndex

Common issues when connecting HiDeliver to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

HiDeliver + LlamaIndex FAQ

Common questions about integrating HiDeliver MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query HiDeliver tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.