SingleStore MCP Server for LlamaIndex 6 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add SingleStore as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
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 SingleStore. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in SingleStore?"
)
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 SingleStore MCP Server
Grant your AI agent (like Claude or Cursor) absolute read-and-write sovereignty over your SingleStore infrastructure. The SingleStore MCP equips your LLM to act as a fully autonomous database administrator. Stop navigating external dashboards to check schema details or run complex search queries.
LlamaIndex agents combine SingleStore tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through the 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
- Execute SQL Queries — Execute raw SQL natively from your AI agent using
execute_sql. - Semantic Vector Search — Perform semantic vector similarity searches natively against your data with
vector_search. - Workspace & Billing Administration — Survey your server clusters with
list_workspaces, list databases withlist_databases, and audit billing usage viaget_billing_usage.
The SingleStore MCP Server exposes 6 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 SingleStore to LlamaIndex via MCP
Follow these steps to integrate the SingleStore 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 6 tools from SingleStore
Why Use LlamaIndex with the SingleStore MCP Server
LlamaIndex provides unique advantages when paired with SingleStore through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine SingleStore tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain SingleStore tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query SingleStore, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what SingleStore tools were called, what data was returned, and how it influenced the final answer
SingleStore + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the SingleStore MCP Server delivers measurable value.
Hybrid search: combine SingleStore real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query SingleStore 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 SingleStore for fresh data
Analytical workflows: chain SingleStore queries with LlamaIndex's data connectors to build multi-source analytical reports
SingleStore MCP Tools for LlamaIndex (6)
These 6 tools become available when you connect SingleStore to LlamaIndex via MCP:
execute_sql
Use read-only SQL statements whenever possible. Executes a SQL query on a SingleStore database
get_billing_usage
Retrieves billing and usage metrics
list_databases
Lists all databases within a specific workspace
list_organizations
Lists organizations associated with the account
list_workspaces
Lists all SingleStore workspaces
vector_search
Performs a DOT_PRODUCT vector similarity search
Example Prompts for SingleStore in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with SingleStore immediately.
"List all my available workspaces."
"List all databases within workspace ID 1234, and then find the first 5 records in 'users_db'."
Troubleshooting SingleStore MCP Server with LlamaIndex
Common issues when connecting SingleStore to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSingleStore + LlamaIndex FAQ
Common questions about integrating SingleStore 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 SingleStore 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 SingleStore to LlamaIndex
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.