Snowflake MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Cancel Sql, Describe Table, Execute Sql, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Snowflake 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 Snowflake app connector for LlamaIndex is a standout in the Industry Titans 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 Snowflake. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Snowflake?"
)
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 Snowflake MCP Server
Connect your Snowflake account to any AI agent to automate your data cloud operations and analytical workflows. Snowflake provides a premier platform for data warehousing and analysis, and this integration allows you to execute SQL statements, browse database schemas, and monitor session contexts through natural conversation.
LlamaIndex agents combine Snowflake 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
- SQL Query Orchestration — Execute any SQL statement programmatically and retrieve real-time data results for immediate analysis.
- Database & Schema Oversight — List and search through databases, schemas, and tables to maintain a clear overview of your data architecture directly from the AI interface.
- Warehouse & Resource Control — Access and monitor available warehouses and user roles to ensure your analytical environment is properly configured.
- Metadata Intelligence — Describe table structures and retrieve session context metadata via natural language commands to facilitate data exploration.
- Operational Monitoring — Track statement execution status and cancel long-running queries to ensure your data cloud resources are used efficiently.
The Snowflake 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 Snowflake tools available for LlamaIndex
When LlamaIndex connects to Snowflake through Vinkius, your AI agent gets direct access to every tool listed below — spanning sql-query, data-warehousing, cloud-data, 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.
Cancel a running SQL statement
Get table schema details
Returns the first partition of results or a handle for long-running queries. Execute a SQL statement in Snowflake
Get current session context
Check the status of a SQL statement
List all accessible databases
List security roles
List schemas in a database
List tables in a schema or database
List Snowflake users
List compute warehouses
Connect Snowflake to LlamaIndex via MCP
Follow these steps to wire Snowflake 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 Snowflake MCP Server
LlamaIndex provides unique advantages when paired with Snowflake through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Snowflake tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Snowflake tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Snowflake, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Snowflake tools were called, what data was returned, and how it influenced the final answer
Snowflake + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Snowflake MCP Server delivers measurable value.
Hybrid search: combine Snowflake real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Snowflake 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 Snowflake for fresh data
Analytical workflows: chain Snowflake queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Snowflake in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Snowflake immediately.
"List all tables in the 'SALES' schema of the 'PROD' database."
"Show me the warehouse usage and query performance metrics for all active Snowflake warehouses."
"Run a SQL query to get the top 10 customers by revenue from the sales table this quarter."
Troubleshooting Snowflake MCP Server with LlamaIndex
Common issues when connecting Snowflake to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSnowflake + LlamaIndex FAQ
Common questions about integrating Snowflake MCP Server with LlamaIndex.