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fabdendev

dagster-mcp

by fabdendev

Get Instance Status

get_instance_status

Check overall health of a Dagster instance: daemon status, code location errors, and queued runs. Use as the first step for monitoring or diagnosing pipeline issues.

Instructions

Get a global health check of the Dagster instance. START HERE for any monitoring workflow.

Returns:

  • healthy: boolean — true only if all required daemons are healthy AND no code locations have errors

  • daemons: list of {type, healthy, last_heartbeat, required} for each daemon (scheduler, sensor, run coordinator, etc.)

  • queued_runs_count: number of runs waiting in queue (high count = bottleneck)

  • queued_runs_count_capped: true when the count is a floor rather than exact, which happens only on Dagster versions that do not report a total

  • code_location_errors: list of {name, error} for locations that failed to load

When to use: as the FIRST call in any diagnostic or monitoring flow. If healthy=false, check daemons for unhealthy entries and code_location_errors for loading failures. Follow up with list_code_locations or get_runs as needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden, and it delivers substantive behavioral context the schema cannot: the exact semantics of 'healthy' (all required daemons healthy AND no code location errors), the meaning of a high queued_runs_count, and that queued_runs_count_capped signals a floor rather than exact count on certain versions. It does not state the read-only/side-effect profile explicitly or mention auth or rate limits, so it falls short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and the 'START HERE' directive, then a scannable Returns list and a When-to-use block. Some bullets restate field shapes that the output schema already defines, so it is slightly longer than strictly necessary, but it is well organized and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so enumerating return fields is partly redundant, but the description adds interpretation (bottleneck signal, capped-count caveat, health preconditions) that an agent needs to act on the result. The only real gap is the unexplained 'env' parameter; otherwise the definition is complete for a zero-required-param health check.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description never mentions the single 'env' parameter, so an agent gets no guidance on what it selects or when to supply it. With one undocumented parameter, the description does not compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get a global health check of the Dagster instance') and frames the scope as global/instance-level, which cleanly separates it from run-level siblings like get_run_status or get_run_stats. The 'START HERE for any monitoring workflow' line further anchors its role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use guidance: first call in any diagnostic or monitoring flow, with a concrete branching rule (if healthy=false, check daemons and code_location_errors) and named follow-ups (list_code_locations, get_runs). Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.