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sandraschi

Observability MCP Server

export_metrics

Export collected metrics as Prometheus, OpenTelemetry, or JSON to integrate observability data with external monitoring systems, optionally including historical data.

Instructions

Export collected metrics in various formats for external monitoring systems.

Supports Prometheus, OpenTelemetry, and JSON formats for integration with existing monitoring infrastructure.

Input Schema

NameRequiredDescriptionDefault
formatNoExport format (prometheus, opentelemetry, json)prometheus
include_historyNoWhether to include historical data

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It never says whether export is a pull/read operation or a side-effecting push, whether output is returned inline or written to a file/endpoint, what include_history costs in volume, or what permissions are needed. Only the format enumeration is disclosed, which the schema already covers.

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?

Two short sentences that lead with the core action. The second sentence largely restates the format list already present in the schema, so it earns its place only partially, but there is no filler.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the tool is simple with two optional parameters. However, for a tool with zero annotations, the description omits whether the export is read-only, how data is delivered, and how it relates to the metric-collection and reporting siblings, leaving an agent with gaps before calling it.

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% and both parameters (format, include_history) are documented with defaults and allowed values in the schema itself. The description repeats the format names but adds no syntax, sizing, or trade-off detail beyond the schema, so baseline 3 applies.

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 a specific verb and resource ('Export collected metrics') plus the supported output formats. It is reasonably distinguishable from siblings like collect_performance_metrics or generate_performance_reports, though it never explicitly contrasts itself with them.

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

Usage Guidelines3/5

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

Usage is only implied through the phrase 'for external monitoring systems' and 'integration with existing monitoring infrastructure.' There is no explicit guidance on when to choose this over collect_performance_metrics or generate_performance_reports, nor any stated prerequisites.

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