Claude MCP Server

Overview

The Upsolve AI MCP server connects Claude to your data warehouse, turning plain-English questions into SQL queries, charts, and AI-generated insights — all rendered as an interactive panel inside your Claude conversation. Unlike generic text-to-SQL tools, Upsolve brings your team’s institutional knowledge into every answer: your KPI definitions, validated SQL patterns, business logic rules, and behavioral guardrails are all encoded into the agent before it ever sees a question. The result is answers you can trust, not just answers that look right. Server URL: https://mcp.upsolve.ai/mcp Transport: Streamable HTTP Auth: OAuth 2.0

The Upsolve MCP server is read-only. It never writes, modifies, or deletes data in your connected data sources.

What You Get

When Claude calls the Upsolve MCP, results are returned as an interactive panel rendered directly in the conversation — no tab switching, no copy-pasting SQL. Each response includes:

Component	Description
AI insights	Plain-English summary of key findings
Charts	Auto-generated bar, line, pie, and other visualizations
Data table	Sortable results with CSV export

Multi-turn follow-ups are supported — Claude maintains conversation context across questions in the same thread.

Prerequisites

Before connecting, make sure you have:

An active Upsolve AI account — start a free trial at upsolve.ai (no credit card required)
At least one data source connected in Upsolve (Snowflake, BigQuery, Amazon Redshift, PostgreSQL, or any JDBC/ODBC-compatible warehouse)
Claude.ai or Claude Desktop — either works

If you haven’t connected a data source yet, go to your Upsolve workspace → Connect tab → choose your warehouse. A sample database is available if you want to test before connecting your own data.

Connecting to Claude

Claude.ai (web)
Claude Desktop
Claude Code

Open Connectors settings

Go to claude.ai → click your profile icon → Settings → Connectors.

Add a custom connector

Click Add custom connector (or search for Upsolve if it appears in the directory).

Enter the server URL

Paste the server URL:

https://mcp.upsolve.ai/mcp

Claude will redirect you to Upsolve’s OAuth sign-in. Log in with your Upsolve account credentials. You’ll be redirected back to Claude once authorized.

Enable in your conversation

Open a new Claude conversation. Toggle the Upsolve connector on in the toolbar. You’re ready to ask your first question.

Open Connector settings

Open Claude Desktop → Settings → Connectors → Add custom connector.

Enter the server URL

Paste the server URL:

https://mcp.upsolve.ai/mcp

A browser window will open prompting you to sign in to your Upsolve account via OAuth. Complete sign-in and return to Claude Desktop.

Start asking questions

Open a new conversation. The Upsolve connector is active automatically.

Add the following to your MCP configuration file:

{
  "mcpServers": {
    "upsolve": {
      "url": "https://mcp.upsolve.ai/mcp",
      "transport": "streamable-http"
    }
  }
}

Run claude mcp add or update your .mcp.json directly. Authenticate via OAuth when prompted.

Authentication

Upsolve MCP uses OAuth 2.0. When you connect for the first time, Claude redirects you to sign in to your Upsolve account. Your Upsolve credentials are never shared with Claude or Anthropic — only a short-lived OAuth access token is passed to authorize requests.

Tokens are scoped to your Upsolve account and the data sources you have access to
Revoking access is instant: go to your Upsolve account → Settings → Connected Apps and remove Claude

Available Tools

`analyze_data`

The core tool. Ask any analytical question in plain English — Upsolve’s agent generates and executes SQL against your connected data source and returns results as an interactive panel inside Claude. Inputs:

Parameter	Type	Required	Description
`message`	string	Yes	Your question or data request in plain English
`thread_id`	string	No	Thread ID to continue a multi-turn conversation

Returns: An interactive MCP App panel with AI insights, charts, and a sortable data table. Annotations: readOnlyHint: true — this tool only reads data, never writes or modifies anything.

Claude manages thread_id automatically in multi-turn conversations — you don’t need to set it manually. Just keep asking follow-up questions in the same chat thread.

Example Prompts

Explore and summarize databases and datasets

These prompts help you understand what data is available and get high-level summaries before diving into specifics.

What tables are in my connected data source, and what does each one contain?

Summarize the key metrics in my sales dataset for last quarter.

What are the top-level trends in my data over the past 12 months?

Show me a breakdown of records by status across all order tables.

Generate and execute data logic for visualization

These prompts produce charts and visual outputs — Upsolve generates the SQL, runs it, and renders the chart inline.

Create a bar chart showing monthly revenue by product category for the last 6 months.

Show me a trend line of daily active users over the past 30 days.

Build a visualization comparing conversion rates across our marketing channels this quarter.

Plot customer acquisition by region as a stacked area chart, month by month.

Generate data insights from analytics

These prompts ask Upsolve to interpret results and surface what matters — not just data, but the “so what.”

What are the key takeaways from our Q3 sales performance?

Which customer segments are showing the highest churn risk this month?

Identify any anomalies or outliers in this week's transaction data.

Why did revenue drop in October? Walk me through the most likely causes.

Multi-turn Conversations

Upsolve supports multi-turn analytical conversations — you can refine, drill down, and pivot across follow-up questions without losing context. Claude manages conversation continuity automatically via thread_id. You don’t need to repeat context between questions in the same conversation thread. Example conversation:

You: Show me revenue for Q3 broken down by product line. (Upsolve returns a chart and table) You: Now filter to just enterprise customers. (Upsolve refines the same query with the new filter) You: Which product line had the highest month-over-month growth? (Upsolve adds a growth calculation to the existing analysis)

How Upsolve Produces Reliable Answers

Generic text-to-SQL tools connect to your schema — and that’s it. Answers look right in a demo and fail in production because they have no context for how your business actually works. Upsolve encodes six layers of institutional context into the agent before it answers any question:

Layer	What it encodes
Data model & schema	Tables, columns, and relationships
KPI definitions	Both the technical SQL and the plain-English business meaning
Validated SQL patterns	Your team’s known-good queries for common questions
Business rules	Edge cases, filters, and logic specific to your data
Behavioral guardrails	What the agent should and should not answer
Column descriptions	Business-language labels for technical column names

This is what makes the difference between an agent that hallucinates in front of the CFO and one your team actually relies on.

To add or update context for your agent, go to your Upsolve workspace → Agent Studio → select your agent → open the relevant context tab. Changes take effect on the next query.

Security & Data Handling

Read-only access — the analyze_data tool carries readOnlyHint: true. It queries your data; it never modifies it.
Data scoping — the agent only has access to the data sources connected in your Upsolve account. It cannot query data outside that scope.
No data retention — queries execute in real-time. Upsolve does not store your query results or conversation content beyond the session.
Encrypted in transit — all data transmitted between Claude, Upsolve’s MCP server, and your data source is encrypted via HTTPS/TLS.
Your credentials stay with you — your data warehouse credentials are stored in Upsolve, not passed to Claude or Anthropic.

For full details, see the Upsolve Privacy Policy.

Troubleshooting

Claude says it can't find the Upsolve connector

Make sure the connector is toggled on for your current conversation — look for the Upsolve icon in the conversation toolbar. If it doesn’t appear, go to Settings → Connectors and confirm the server URL is https://mcp.upsolve.ai/mcp.

Authentication failed or OAuth loop

Try disconnecting and reconnecting the integration:

Go to Settings → Connectors in Claude
Remove the Upsolve connector
Re-add it with the server URL https://mcp.upsolve.ai/mcp
Complete the OAuth sign-in flow again

If the issue persists, check that your Upsolve account is active at upsolve.ai and that you’re signing in with the correct credentials.

Upsolve returns an error about no data source connected

The agent needs at least one connected data source to answer questions. Go to your Upsolve workspace → Connect tab → connect a data warehouse. If you want to test without your own data, use the sample database available in the Connect tab.

Answers look wrong or don't match what I expect

This usually means the agent is missing context about your specific data or business logic. In your Upsolve workspace, go to Agent Studio → select your agent and review:

KPI definitions — are your key metrics defined with both SQL and business-language descriptions?
Golden assets — have you added validated SQL patterns for common questions?
Business rules — are there edge cases or filters that should always apply?

The more context you encode, the more reliable the answers become.

The interactive panel isn't rendering in Claude

The interactive chart and table panel requires Claude.ai (web) or Claude Desktop with MCP App support enabled. Claude Code displays results as structured text instead of an interactive panel — all data is still returned, just without the visual UI.

Next Steps

Connect a Data Source

Link your Snowflake, BigQuery, Redshift, or PostgreSQL warehouse to Upsolve.

Build Your Agent

Set up KPI definitions, golden assets, and behavioral guardrails in Agent Studio.

Test Before You Ship

Run your agent against a golden query set before exposing it to business users.

Deploy to Other Surfaces

Embed your analytics agent in your product, Slack, or other MCP-compatible tools.

Support

Email: support@upsolve.ai
Website: upsolve.ai
Privacy Policy: upsolve.ai/privacy

Welcome to Upsolve AI

Get Started

Concepts

Encode Your Context

Deploy & Expose

Observability

Technical Reference

Overview

What You Get

Prerequisites

Connecting to Claude

Authentication

Available Tools

`analyze_data`

Example Prompts

Explore and summarize databases and datasets

Generate and execute data logic for visualization

Generate data insights from analytics

Multi-turn Conversations

How Upsolve Produces Reliable Answers

Security & Data Handling

Troubleshooting

Next Steps

Connect a Data Source

Build Your Agent

Test Before You Ship

Deploy to Other Surfaces

Support

Welcome to Upsolve AI

Get Started

Concepts

Encode Your Context

Deploy & Expose

Observability

Technical Reference

​Overview

​What You Get

​Prerequisites

​Connecting to Claude

​Authentication

​Available Tools

​analyze_data

​Example Prompts

​Explore and summarize databases and datasets

​Generate and execute data logic for visualization

​Generate data insights from analytics

​Multi-turn Conversations

​How Upsolve Produces Reliable Answers

​Security & Data Handling

​Troubleshooting

​Next Steps

Connect a Data Source

Build Your Agent

Test Before You Ship

Deploy to Other Surfaces

​Support

Overview

What You Get

Prerequisites

Connecting to Claude

Authentication

Available Tools

`analyze_data`

Example Prompts

Explore and summarize databases and datasets

Generate and execute data logic for visualization

Generate data insights from analytics

Multi-turn Conversations

How Upsolve Produces Reliable Answers

Security & Data Handling

Troubleshooting

Next Steps

Support