Smaily MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Create Subscriber, Delete Subscriber, Get Automation, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Smaily 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 Smaily app connector for LlamaIndex is a standout in the Marketing Automation category — giving your AI agent 11 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 Smaily. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Smaily?"
)
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 Smaily MCP Server
Connect your Smaily account to any AI agent and simplify your email marketing and automation workflows through natural conversation.
LlamaIndex agents combine Smaily tool responses with indexed documents for comprehensive, grounded answers. Connect 11 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
- Subscriber Management — List all contacts in your database, retrieve detailed profile metadata, and create new subscribers programmatically
- Campaign Control — Query past and scheduled email campaigns to monitor your marketing outreach
- Automation & Autoresponders — List configured automated workflows and trigger specific autoresponder emails directly from your agent
- Template catalog — Query available email templates to choose the right look for your messages
- Operational tracking — Stay on top of your marketing performance and subscriber engagement
The Smaily MCP Server exposes 11 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 11 Smaily tools available for LlamaIndex
When LlamaIndex connects to Smaily through Vinkius, your AI agent gets direct access to every tool listed below — spanning subscriber-management, campaign-tracking, email-automation, 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.
Add a new subscriber
Remove a subscriber
Get details for an automation workflow
Get details for a specific campaign
Get details for a specific subscriber
Get details for an email template
List automated responders
List email campaigns
List message templates
List Smaily subscribers
Trigger an automation email
Connect Smaily to LlamaIndex via MCP
Follow these steps to wire Smaily 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 Smaily MCP Server
LlamaIndex provides unique advantages when paired with Smaily through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Smaily tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Smaily tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Smaily, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Smaily tools were called, what data was returned, and how it influenced the final answer
Smaily + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Smaily MCP Server delivers measurable value.
Hybrid search: combine Smaily real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Smaily 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 Smaily for fresh data
Analytical workflows: chain Smaily queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Smaily in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Smaily immediately.
"List all subscribers in Smaily."
"Show me the campaign performance for all email campaigns sent this quarter with engagement trends."
"Create a new subscriber and add them to the VIP customer automation workflow."
Troubleshooting Smaily MCP Server with LlamaIndex
Common issues when connecting Smaily to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSmaily + LlamaIndex FAQ
Common questions about integrating Smaily MCP Server with LlamaIndex.