Skip to main content
Glama
fabdendev

dagster-mcp

by fabdendev

get_run_logs

Fetch structured log events for a run with optional severity filtering and pagination. Use for detailed run investigation when a failure summary is insufficient.

Instructions

Get structured log events for a run, with optional severity filtering and pagination.

Returns events with __typename, timestamp, message, level, and (where applicable) stepKey and error details. Events include step starts/completions, failures, retries, materializations, and run-level events. EngineEvent events also carry metadataEntries — a list of {label, description, value} dicts (e.g. run worker image, k8s pod name, step keys) surfaced by the engine.

Parameters:

  • run_id: the run to fetch logs for

  • level_filter: only return events at this level or above. Values: 'DEBUG', 'INFO', 'WARNING', 'ERROR'. When set to 'ERROR', also includes ExecutionStepFailureEvent and RunFailureEvent regardless of their level field. Default: None (return all events).

  • cursor: pagination cursor returned in previous response. Pass the cursor from the last call to get the next page.

  • limit: max events per page (default 100)

When to use: to investigate what happened during a run. For a quick failure diagnosis, prefer get_run_failure_summary instead — it returns a consolidated view in a single call. Use get_run_logs when you need the full event stream or want to filter by level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo
limitNo
cursorNo
run_idYes
level_filterNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. It details return structure (field names, event types), pagination (cursor), filtering behavior, and special case for level_filter=ERROR (includes failure events). No contradictions.

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?

The description is well-structured with sections (parameters, when to use) and avoids fluff. It is slightly long but every sentence adds value. Could be slightly tightened.

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?

Given the tool has an output schema, the description doesn't need to fully detail return values but does so helpfully. It covers event types and fields. However, it omits the 'env' parameter, which is a small gap. Overall adequate for the complexity.

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

Parameters3/5

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

Schema coverage is 0%, so description must explain parameters. It explains run_id, level_filter (values and special behavior), cursor, and limit default. However, the 'env' parameter is missing from the description entirely, leaving it undocumented.

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?

The description clearly states the tool's purpose: 'Get structured log events for a run, with optional severity filtering and pagination.' It specifies the resource (run logs) and the action (get), and distinguishes from siblings like get_run_failure_summary.

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?

The description explicitly says 'When to use' and contrasts with get_run_failure_summary: 'For a quick failure diagnosis, prefer get_run_failure_summary... Use get_run_logs when you need the full event stream or want to filter by level.'

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/fabdendev/dagster-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server