SleekFlow MCP Server for LlamaIndex 7 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SleekFlow 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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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 SleekFlow. "
"You have 7 tools available."
),
)
response = await agent.run(
"What tools are available in SleekFlow?"
)
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 SleekFlow MCP Server
Connect your SleekFlow platform to any AI agent to power up your conversational support, sales, and marketing. Read real-time chat threads spanning across multiple digital channels and dispatch replies without leaving your chat interface.
LlamaIndex agents combine SleekFlow tool responses with indexed documents for comprehensive, grounded answers. Connect 7 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
- Unified Conversations — Track and retrieve ongoing chat histories across WhatsApp, Instagram, Telegram, and WeChat
- Direct Messaging — Compose and send outbound responses or proactive messages back to customers seamlessly
- Contact Management — List all synced contacts and get their deep profile metadata including CRM ties
- Chat Segmentation — View categorization labels to segment hot leads or identify VIP support customers
- Automation Overviews — Retrieve a list of your configured automation workflows and active chatbot trees
The SleekFlow MCP Server exposes 7 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 SleekFlow to LlamaIndex via MCP
Follow these steps to integrate the SleekFlow 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 7 tools from SleekFlow
Why Use LlamaIndex with the SleekFlow MCP Server
LlamaIndex provides unique advantages when paired with SleekFlow through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SleekFlow tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SleekFlow tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SleekFlow, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SleekFlow tools were called, what data was returned, and how it influenced the final answer
SleekFlow + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SleekFlow MCP Server delivers measurable value.
Hybrid search: combine SleekFlow real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SleekFlow 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 SleekFlow for fresh data
Analytical workflows: chain SleekFlow queries with LlamaIndex's data connectors to build multi-source analytical reports
SleekFlow MCP Tools for LlamaIndex (7)
These 7 tools become available when you connect SleekFlow to LlamaIndex via MCP:
get_contact_details
Retrieves details for a specific contact
list_automation_flows
Lists available automation flows
list_channels
Lists all connected communication channels
list_contact_labels
Lists all labels used for contact categorization
list_contacts
Lists all contacts in SleekFlow
list_conversations
Lists all conversations across channels
send_message
Sends a message in a conversation
Example Prompts for SleekFlow in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with SleekFlow immediately.
"Show me all unread conversations from this weekend."
"Send a reply to conversation conv-xxxx saying 'Your refund has been processed. It will appear in 3-5 business days.'"
Troubleshooting SleekFlow MCP Server with LlamaIndex
Common issues when connecting SleekFlow to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSleekFlow + LlamaIndex FAQ
Common questions about integrating SleekFlow 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 SleekFlow 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 SleekFlow to LlamaIndex
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.