Flodesk MCP Server for LlamaIndex 12 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Flodesk 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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Vinkius supports streamable HTTP and SSE.
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 Flodesk. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Flodesk?"
)
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 Flodesk MCP Server
Connect your Flodesk account to any AI agent and automate your email marketing and audience management through the Model Context Protocol (MCP). Flodesk is designed for creators and businesses that want to build stunning emails and automate their sales funnels with ease. Now, you can manage your subscribers, organize your segments, and trigger automated workflows directly through natural conversation.
LlamaIndex agents combine Flodesk tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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 email subscribers, fetch detailed profile data, and create or update subscriber records instantly.
- Audience Segmentation — Access and list your segments, and add subscribers to specific groups to ensure targeted messaging.
- Workflow Automation — List your automated email sequences and trigger specific workflows for new or existing subscribers.
- Opt-out Handling — Unsubscribe users directly through the agent to maintain a clean and compliant mailing list.
- Custom Data Fields — List and create custom subscriber fields to store specific metadata (e.g., interests, purchase history).
- Form Oversight — Retrieve a list of all your opt-in forms to monitor where your audience is coming from.
- Account Insights — Fetch your Flodesk account metadata to ensure your agent has the correct context for your branding.
The Flodesk MCP Server exposes 12 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 Flodesk to LlamaIndex via MCP
Follow these steps to integrate the Flodesk 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 12 tools from Flodesk
Why Use LlamaIndex with the Flodesk MCP Server
LlamaIndex provides unique advantages when paired with Flodesk through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Flodesk tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Flodesk tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Flodesk, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Flodesk tools were called, what data was returned, and how it influenced the final answer
Flodesk + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Flodesk MCP Server delivers measurable value.
Hybrid search: combine Flodesk real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Flodesk 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 Flodesk for fresh data
Analytical workflows: chain Flodesk queries with LlamaIndex's data connectors to build multi-source analytical reports
Flodesk MCP Tools for LlamaIndex (12)
These 12 tools become available when you connect Flodesk to LlamaIndex via MCP:
add_to_segment
Add subscriber to segment
create_custom_field
Create custom field
create_subscriber
Add a subscriber
get_account_details
Get account info
get_subscriber
Get subscriber details
list_custom_fields
List custom subscriber fields
list_forms
List opt-in forms
list_segments
List segments
list_subscribers
List email subscribers
list_workflows
List automation workflows
trigger_workflow
Start workflow for user
unsubscribe_subscriber
Unsubscribe a user
Example Prompts for Flodesk in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Flodesk immediately.
"List my 10 most recent email subscribers."
"Add 'hello@newlead.com' to my 'Welcome' segment and trigger the 'Onboarding' workflow."
"Show me all my active automation workflows."
Troubleshooting Flodesk MCP Server with LlamaIndex
Common issues when connecting Flodesk to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpFlodesk + LlamaIndex FAQ
Common questions about integrating Flodesk MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Flodesk with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Flodesk to LlamaIndex
Get your token, paste the configuration, and start using 12 tools in under 2 minutes. No API key management needed.