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Connect your AI assistant to Costory and explore cloud costs, compare spending, set up alerts, and share reports, all through natural conversation.

Getting Started

Claude Desktop supports MCP connectors natively. No local server or Node.js required.
  1. Open Claude Desktop settings
  2. Go to Connectors
  3. Click Add custom connector
  4. Enter Costory as the name and https://app-api.costory.io/mcp as the URL
  5. Click Add, then Connect
  6. A browser window will open. Log in with your Costory account
  7. Start asking about your costs
Adding Costory as a custom connector in Claude Desktop
You can also add the server via the developer config file (Developer > Edit Config). This method requires Node.js:
{
  "mcpServers": {
    "costory": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://app-api.costory.io/mcp"]
    }
  }
}
On first connection, a browser window will open for you to log in with your Costory account. The mcp-remote fallback requires Node.js to be installed.

Why Costory MCP?

Direct access to AWS CUR or a GCP MCP server gives you provider-native line items and dimensions. Costory MCP adds your Costory workspace context so you can ask higher-level cost questions and take action in the same flow.
  • Query spend by team, product, or feature because , , and are already modeled.
  • Ask one question across AWS, GCP, Azure, Datadog, Anthropic, OpenAI, and Cursor instead of wiring and maintaining separate MCP servers per provider.
  • Explain why costs moved by using with deploys, Datadog metrics, and provider events in the same investigation.
  • Continue from saved views, dashboards, team structures, alert history, and prior investigations so your assistant has persistent workspace context.
  • Connect with one URL and OAuth (no IAM credentials, Docker, or local server setup), and use it in Claude, Cursor, VS Code, or Claude Code.
  • Take action directly from chat by creating alerts, saving views, logging events, and sending Slack reports.
  • Use pre-computed allocation rules and shared costs so each query starts from resolved context instead of rebuilding logic from raw CUR data.

What You Can Do

Explore Costs

Ask questions in natural language and the assistant will query your cost data:
  • “How much is the payments team spending on compute this month?”
  • “Show me infrastructure costs for the recommendation engine, broken down by service”
  • “What’s our total AI spend across Anthropic, OpenAI, and Bedrock?”
  • “How much are we spending on storage?”

Compare Periods

Understand how costs have changed over time:
  • “What’s driving the cost increase on our data pipeline this week? Any related deploys or traffic changes?”
  • “Did the March 15th release affect our search service costs?”
  • “Compare this week’s spend to last week for the growth team”
  • “How have our compute costs changed compared to last month?”

Find Information

Search across your entire Costory workspace:
  • “Find the saved view for the data team’s Kubernetes costs”
  • “What dashboards do we have for AI spend across providers?”
  • “Show me alert history related to BigQuery pipelines”

Get Recommendations

The assistant can suggest what to look at:
  • “What dimension should I group by to explain the checkout cost spike?”
  • “Based on deploy and metric history, what should I investigate next on the data pipeline increase?”

Take Action

Go beyond analysis. Create views, alerts, events, and share reports:
  • “Save this query as a view called ‘Recommendation Engine Infra Cost’”
  • “Set up an alert if payments team compute costs go above $10,000 this month”
  • “Log an event: deployed search ranking v3 on March 15th”
  • “Send this cross-provider AI cost report to the #finops Slack channel”

Example Conversations

You: “Why did our costs go up last week?”The assistant will:
  1. Query cost differences between last week and the week before
  2. Show which services and dimensions drove the change
  3. Check correlated events in the same period (deploys, metric changes, provider events)
  4. Highlight likely causes with a timeline of what changed first
  5. Suggest follow-up actions (drill deeper, set up an alert, etc.)
You: “What’s our total AI spend across Anthropic, OpenAI, and Bedrock this month? Break it down by team and model.”The assistant will:
  1. Query AI-related spend across Anthropic, OpenAI, and AWS Bedrock
  2. Combine results into one total with a provider-level breakdown
  3. Break down the same spend by team and model
  4. Offer to save the view or send the report to Slack
You: “Show me our top 5 services by cost this month, then send it to #cloud-costs on Slack”The assistant will:
  1. Query costs grouped by service for the current month
  2. Save the query as a view
  3. Send a formatted report with chart to the Slack channel
You: “Create an alert if our daily compute costs go above $5,000”The assistant will:
  1. Create a saved view for compute costs
  2. Set up a cost alert with the threshold
  3. Return a link to review and edit the alert in Costory

Available Tools

ToolWhat it does
searchFind dimensions, dashboards, saved views, events, and metrics in your workspace
query_costsQuery cost data with grouping, filters, and time ranges
get_cost_diffCompare costs between two periods to see what changed
getFetch full details of a dashboard, saved view, or advanced explorer
suggest_groupbyGet recommendations for the best dimension to analyze
create_saved_viewSave a cost query for reuse
create_alertSet up cost threshold alerts with notifications
create_eventLog events to annotate cost changes
list_eventsView logged events in a date range
list_alertsView all active cost and budget alerts
send_to_slackSend a cost report to a Slack channel
list_slack_channelsSee available Slack channels
list_organizationsSee which organizations you have access to

Tips

Be specific about time

“last 30 days”, “this quarter”, “March 2026”. The assistant understands natural date ranges.

Use your own names

Mention service names, team names, or project names. The assistant searches your workspace to find the right dimensions.

Ask follow-ups

After a query, drill deeper: “now filter that to just eu-west-1” or “break that down by SKU”.

Multi-org support

If you belong to multiple organizations, just mention which one: “show costs for acme-prod”.

Troubleshooting

If using Claude Desktop’s native connector, try disconnecting and reconnecting in Settings > Connectors. If using the mcp-remote fallback, make sure npx is available in your PATH.
Make sure you’re using the native HTTP transport (type: "http") rather than mcp-remote. Run /mcp in Claude Code, then select Authenticate to trigger the OAuth flow.
Your session may have expired. Restart the MCP server in your AI client to re-authenticate. In Claude Code, run /mcp and select Authenticate.
Specify which org you want in your message: “show costs for [your-org-slug]”.
Last modified on March 19, 2026