Mailingwork MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Create Subscriber, Get Mailing, Get Subscriber, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Mailingwork as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Mailingwork app connector for LlamaIndex is a standout in the Marketing Automation category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Mailingwork. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Mailingwork?"
)
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 Mailingwork MCP Server
Connect your Mailingwork account to any AI agent and manage email campaigns through natural conversation.
LlamaIndex agents combine Mailingwork tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Campaign Management — Create, schedule, and track email campaigns
- Subscriber Lists — Manage mailing lists with import and segmentation
- Report Analytics — Access open rates, click maps, and delivery metrics
- Deliverability — Monitor bounce rates and sender reputation
- Template Management — Browse and manage email templates
The Mailingwork MCP Server exposes 10 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.
All 10 Mailingwork tools available for LlamaIndex
When LlamaIndex connects to Mailingwork through Vinkius, your AI agent gets direct access to every tool listed below — spanning gdpr-compliant, campaign-management, subscriber-segmentation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new subscriber
Get mailing details
Get subscriber details
List all subscriber lists
List all mailings/campaigns
List all subscribers
List all tags
g., order confirmation). Send a transactional email
Trigger an automated workflow
Update an existing subscriber
Connect Mailingwork to LlamaIndex via MCP
Follow these steps to wire Mailingwork into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Mailingwork MCP Server
LlamaIndex provides unique advantages when paired with Mailingwork through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Mailingwork tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Mailingwork tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Mailingwork, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Mailingwork tools were called, what data was returned, and how it influenced the final answer
Mailingwork + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Mailingwork MCP Server delivers measurable value.
Hybrid search: combine Mailingwork real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Mailingwork 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 Mailingwork for fresh data
Analytical workflows: chain Mailingwork queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Mailingwork in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Mailingwork immediately.
"Show all campaigns and performance for this month."
"Show mailing lists and subscriber growth."
"Show click map and deliverability report for the Spring Newsletter."
Troubleshooting Mailingwork MCP Server with LlamaIndex
Common issues when connecting Mailingwork to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMailingwork + LlamaIndex FAQ
Common questions about integrating Mailingwork MCP Server with LlamaIndex.