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dynatrace-bridge-mcp

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find_metrics

Search the Dynatrace metric catalogue by free text or id pattern to find metric ids, units, aggregations, dimensions, and entity types before querying metrics.

Instructions

Searches the Dynatrace metric catalogue and returns metric ids with unit, available aggregations, dimensions and the entity types they apply to. Use it before query_metrics whenever you are not sure of the exact metric id.

Pass text for a free-text search over id, name and description (e.g. "response time", "container memory", "v8 heap"), and/or selector for an id pattern with a trailing wildcard (e.g. builtin:service.*, builtin:containers.cpu.*, builtin:kubernetes.workload.*, builtin:tech.jvm.*, builtin:tech.nodejs.*).

This tool runs through the Dynatrace Bridge browser extension in the user's logged-in browser. If it fails, report the error to the user; do not try to open browser tabs or use browser automation instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoFree-text search over metric id, display name and description.
limitNoMaximum number of metrics to print. Default 50, at most 200. The output says how many were omitted.
describeNoAlso print each metric's description. Default false.
selectorNoMetric id or id prefix with a trailing `*`, e.g. `builtin:service.*`. Several can be given comma-separated.
environmentNoWhich Dynatrace environment to query, as named in the Dynatrace Bridge extension popup. Omit it for the default, the first environment configured there. The names are not listed here because the extension had not connected yet when this description was built; `dynatrace_bridge_status` lists them.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.7/5.0
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 does disclose a major behavioral trait: execution goes through the Dynatrace Bridge browser extension in the user's logged-in browser. It also gives failure guidance ('report the error to the user; do not try to open browser tabs or automation instead'), which is unusually valuable context. It does not explicitly state read-only semantics for the query.

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?

Three short paragraphs, each with a distinct job: what it returns, how to search, and how it executes. The purpose and the query_metrics routing are front-loaded, and nothing is padded.

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

Completeness5/5

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

With no output schema, the description compensates by enumerating the returned fields (id, unit, aggregations, dimensions, entity types) and by covering execution path and failure handling. Also notes limit/omission behavior. Nothing an agent needs to call this safely is missing.

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

Parameters4/5

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

Schema coverage is 100%, so baseline would be 3, but the description adds real meaning beyond the schema: concrete free-text examples ('response time', 'container memory', 'v8 heap') and concrete selector patterns ('builtin:service.*', 'builtin:kubernetes.workload.*'). That elevates it above the schema baseline.

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 (searches) and resource (Dynatrace metric catalogue) and enumerates what comes back (metric ids, unit, aggregations, dimensions, entity types). It is clearly distinguishable from the sibling query_metrics, which it explicitly references.

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?

Gives an explicit condition for use ('before query_metrics whenever you are not sure of the exact metric id') and names the alternative tool. The reader knows exactly when this tool is the right choice versus query_metrics.

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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