MJML (Email Markup) MCP Server for LlamaIndexGive LlamaIndex instant access to 1 tools to Render Mjml

Name: MJML (Email Markup)
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The MJML (Email Markup) MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 1 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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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 MJML (Email Markup). "
            "You have 1 tools available."
        ),
    )

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

asyncio.run(main())

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About MJML (Email Markup) MCP Server

Connect the MJML engine to your AI agent to generate professional, responsive email templates using natural language. MJML is the industry standard for ensuring emails look great across all clients like Outlook, Gmail, and Apple Mail.

LlamaIndex agents combine MJML (Email Markup) tool responses with indexed documents for comprehensive, grounded answers. Connect 1 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

Responsive Rendering — Convert MJML XML or JSON strings into production-ready HTML in seconds
Email Prototyping — Rapidly iterate on email designs within your chat or code editor
Best Practices — Ensure your markup follows email client standards automatically without manual table hacking

The MJML (Email Markup) MCP Server exposes 1 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 1 MJML (Email Markup) tools available for LlamaIndex

When LlamaIndex connects to MJML (Email Markup) through Vinkius, your AI agent gets direct access to every tool listed below — spanning email-templates, responsive-design, html-rendering, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

render

Render mjml on MJML (Email Markup)

Provide the raw MJML XML or JSON string. Render MJML markup to responsive HTML

Connect MJML (Email Markup) to LlamaIndex via MCP

Follow these steps to wire MJML (Email Markup) into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 1 tools from MJML (Email Markup)

Why Use LlamaIndex with the MJML (Email Markup) MCP Server

LlamaIndex provides unique advantages when paired with MJML (Email Markup) through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine MJML (Email Markup) tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain MJML (Email Markup) tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query MJML (Email Markup), a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what MJML (Email Markup) tools were called, what data was returned, and how it influenced the final answer

MJML (Email Markup) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the MJML (Email Markup) MCP Server delivers measurable value.

Hybrid search: combine MJML (Email Markup) real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query MJML (Email Markup) 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 MJML (Email Markup) for fresh data

Analytical workflows: chain MJML (Email Markup) queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for MJML (Email Markup) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with MJML (Email Markup) immediately.

"Render this MJML code to HTML: <mjml><mj-body><mj-section><mj-column><mj-text>Hello World</mj-text></mj-column></mj-section></mj-body></mjml>"

"Can you use render_mjml to convert a JSON-based MJML structure into a responsive email?"

"Generate a responsive button in MJML and render it to HTML."

Troubleshooting MJML (Email Markup) MCP Server with LlamaIndex

Common issues when connecting MJML (Email Markup) to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

MJML (Email Markup) + LlamaIndex FAQ

Common questions about integrating MJML (Email Markup) 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 MJML (Email Markup) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.