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Common tasks with Tiger CLI and Tiger MCP

Manage services and work with your data in Tiger Cloud using Tiger CLI commands or Tiger MCP natural-language prompts

Tiger CLI and Tiger MCP let you work with Tiger Cloud in complementary ways. With Tiger CLI you run commands in a terminal, which is precise, scriptable, and repeatable. With Tiger MCP you ask your AI agent in plain language: it runs the same service and data operations, and it can also reason about your database using built-in skills.

There are two levels to work at: managing your services, which has no SQL, and working with your data, which is all SQL. The examples below show the CLI way, and the equivalent Tiger MCP prompt. New to these tools? See Tiger CLI and Tiger MCP.

Before you start

Install Tiger CLI and connect your AI agent first. Commands and tools can change between releases, so run tiger --help for the current CLI, and see the Tiger CLI reference and Tiger MCP reference. For agent safety, see best practices for AI agents.

Manage your services

Section titled “Manage your services”

Every service task is a tiger service command in the CLI, and the MCP has a matching tool, so you can instead just describe what you want:

TaskCLI commandAsk your agent
Create a servicetiger service create --name analytics --region us-east-1"Create a time-series service called analytics in us-east-1."
Fork a service to test a change safelytiger service fork <id> --now"Fork service abc123 so I can test a schema change."
Resize a servicetiger service resize <id> --cpu 4 --memory 16"Resize service abc123 to 4 CPU and 16 GB."
Start or stop a servicetiger service start <id>, tiger service stop <id>"Stop service abc123."
Rotate the database passwordtiger service update-password <id>"Reset the password on service abc123."
List, inspect, and check logstiger service list, tiger service get <id>, tiger service logs <id> --tail 100"List my services and show recent logs for abc123."

For the full walkthroughs, see create a service, fork services, change compute resources, and service management.

Work with your data

Section titled “Work with your data”

Everything inside the database is SQL. With Tiger CLI, open a session and run it (add --read-only for a session that blocks writes):

Terminal window
tiger db connect <service-id>

With Tiger MCP, you skip the connection and describe the task, and the agent runs the SQL against the service you name.

For example, to create a hypertable:

CREATE TABLE metrics (
  time   timestamptz NOT NULL,
  device text,
  value  double precision
) WITH (tsdb.hypertable, tsdb.partition_column = 'time');

Or ask "Create a hypertable called metrics partitioned by time, with device and value columns."

The same pattern covers the rest of your everyday data work. Run the SQL yourself, or describe it to your agent:

  • Query your data, for example "What is the hourly average value in metrics over the last day?" See Query data.
  • Load data from a file with \COPY, or ask your agent to add small amounts, for example "Insert a few sample rows into metrics for testing." For bulk loads, see Import data.
  • Roll up a continuous aggregate, for example "Create a continuous aggregate on metrics for hourly averages per device." See Continuous aggregates.
  • Add compression and retention, for example "Convert metrics chunks older than 7 days to the columnstore and drop data older than 30 days." See Hypercore and retention.

Analyze, design, and optimize with Tiger MCP

Section titled “Analyze, design, and optimize with Tiger MCP”

Some data work goes beyond running SQL. Using its built-in skills, Tiger MCP can reason about your database, which the CLI cannot do. Because these tasks are read and advice oriented, they work in read-only mode:

  • Design a schema: "Design a Tiger Cloud schema for storing IoT device telemetry." See Design your data model.
  • Find hypertable candidates: "Analyze my database and tell me which tables should be hypertables." See Choose your migration approach.
  • Review and optimize: "Review my schema and indexes against best practices and suggest improvements." See Improve hypertable performance.
  • Plan a schema change: "Plan a zero-downtime migration to add a status column to metrics, and test it on a fork first." See Alter table schema.

Next steps

Section titled “Next steps”