How to Use the USGS Water Services MCP in LlamaIndex

Q: Can I query metadata alongside flow rates using USGS Water Services with LlamaIndex?

Yes. You can run getsites to get site attributes and then combine that information into the index alongside results from getdailyvalues. The RAG application treats them as one unified data source.

Q: Does LlamaIndex handle filtering for USGS Water Services?

Yes. You can set allowedtools filters when building the agent, ensuring that the underlying MCP Server only exposes tools you want to search against, like getstatistics.

Index USGS Water Services results into LlamaIndex for deep knowledge search.

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Connect USGS Water Services MCP to LlamaIndex

Create your Vinkius account to connect USGS Water Services to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup USGS Water Services with LlamaIndex

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Perplexity

Search and ground water data in RAG.

Running a query on `get_groundwater_levels` doesn't just give you a table; it indexes the resulting historical records into your vector store. Later, when you ask questions about 'low levels in 2018,' LlamaIndex searches that indexed data chunk for grounded answers. The output from tools like `get_daily_values` becomes part of your searchable knowledge base. You can query past sessions or configurations and get answers based on actual USGS API data, not guesses.

Combine live data with site metadata.

Need to know the current flow rate and also what type of sensor was used? Run `get_instantaneous_values` first. LlamaIndex captures that output and combines it with results from `get_sites`, which provides detailed metadata about the location. The result is a unified index entry. You can query the combination—'What's the current flow rate at this specific USGS site, and what are its sensor specs?'—and get an answer citing both data sources.

Query historical statistics efficiently.

Instead of just getting a number from `get_statistics`, LlamaIndex indexes the full statistical report (daily, monthly, annual). This allows you to ask semantic questions like, 'How did the average flow change between 2019 and 2021?' The agent builds RAG applications where live USGS API data is combined with documents. You can query historical trends across different timeframes without manually processing large CSV exports.

Setup guide

Set up USGS Water Services MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all USGS Water Services MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to USGS Water Services tools.",
)
response = await agent.run("List recent USGS Water Services data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by USGS Water Services. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about USGS Water Services MCP in LlamaIndex

You pass the MCP Server tools to a FunctionAgent. When an agent calls `get_instantaneous_values`, LlamaIndex catches that output and indexes it, making the resulting water data part of your searchable knowledge base.

Yes. You can run `get_sites` to get site attributes and then combine that information into the index alongside results from `get_daily_values`. The RAG application treats them as one unified data source.

It's excellent. You can query across different tool outputs—like combining groundwater levels (`get_groundwater_levels`) with site metadata—and get answers grounded in the actual data, eliminating hallucinations.

Yes. You can set `allowed_tools` filters when building the agent, ensuring that the underlying MCP Server only exposes tools you want to search against, like `get_statistics`.

The server touches structured historical and near real-time water data. By indexing the output, LlamaIndex keeps a verifiable record of what was queried and retrieved.

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