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dynatrace-oss

Dynatrace Managed MCP Server

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dynatrace_managed_list_problems

Read-only

List problems from Dynatrace Managed environments using filters for status, impact, time, and entity. Identify open or resolved issues with targeted queries.

Instructions

List problems from the Managed cluster with optional filtering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd time (default: "now")
fromNoStart time (default: "now-24h")
sortNoSort order. Use "+status" (open first), "-status" (closed first), "+startTime" (old first), "-startTime" (new first), or "+relevance"/"-relevance" (with text search).
limitNoMaximum number of problems to return. Use this when user specifies a count (e.g., "first 10 problems" → limit: 10). If not specified, returns up to API limit: 50. Cannot exceed 50
statusNoProblem status - use "OPEN" for active issues, "CLOSED" for resolved problems
impactLevelNoImpact level - use "SERVICE" for application issues, "INFRASTRUCTURE" for host/container problems, "APPLICATION" for user-facing issues
entitySelectorNoEntity selector to filter problems. CRITICAL: Only ONE entity type per query. Use discover_entities() first to get exact names/IDs, then use entityId("exact-id") or type(SERVICE),entityName.equals("exact-name"). Examples: entityId("SERVICE-123"), type(SERVICE),entityName("payment-service"), type(AWS_LAMBDA_FUNCTION),tag("AWS_REGION:us-west-2")
environment_aliasYesSpecify which environment to be queried, by supplying the environment alias as returned by get_environments_info. Can use `ALL_ENVIRONMENTS` to retrieve data from all environments in one request to MCP.

TDQS

B3.4/5.0
Behavior3/5

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

The readOnlyHint annotation already covers the safety profile, and the description is consistent with it. It adds the 'Managed cluster' scope and the notion of optional filtering, but does not disclose pagination, result shape, or time-window defaults beyond what the schema already states.

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

Conciseness5/5

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

One short, front-loaded sentence with no filler. It communicates the core action and optionality efficiently, and every word contributes to the meaning.

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?

For a read-only list operation backed by a rich 100%-covered input schema, the description is nearly complete. It does not mention output shape or sibling-selection guidance, but these are largely inferable from the tool name and the sibling list.

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 description coverage is 100%, so the schema already documents every parameter with meaningful details, including enum values and entitySelector examples. The description itself adds no parameter-level semantics, but the full coverage justifies the baseline score.

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

Purpose4/5

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

States the verb 'List' and the resource 'problems' with a scope qualifier ('from the Managed cluster'). It clearly identifies the operation, but does not explicitly distinguish itself from siblings like get_problem_details or list_events, so it stops short of a 5.

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

Usage Guidelines2/5

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

The description offers no guidance about when to use this tool versus alternatives such as get_problem_details for individual problems or list_events for event data. 'Optional filtering' is a generic hint that does not help an agent choose correctly among siblings.

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

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