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OTEL MCP Server

get_operation_stats

Retrieve latency percentiles and error rates for a service or operation to analyze performance. Filter by time range or specific operation for targeted diagnostics.

Instructions

Get performance statistics for a service or operation.

Args: service_name: Service name (required for Jaeger) operation_name: Filter by specific operation start_time: Start time in ISO 8601 format end_time: End time in ISO 8601 format

Returns: JSON string with latency percentiles and error rates

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_timeNo
start_timeNo
service_nameYes
operation_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

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 implies a read operation via 'Get' and mentions a backend (Jaeger) for service_name, but discloses nothing about permissions, rate limits, or read-only guarantees. The 'Returns' line is largely redundant given the output schema exists.

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-loads the purpose and then cleanly separates Args and Returns sections with no filler. The Args block duplicates parameter names the schema already lists, a minor redundancy, but the overall structure is efficient and easy to scan.

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?

With an output schema present, return values need not be spelled out; parameters are fully documented despite 0% schema coverage; and the tool's read nature is inferable from 'Get'. The main gap is the missing routing guidance against the many overlapping siblings.

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 description coverage is 0%, so the description must compensate, and it does: it documents all four parameters, marks service_name as required (noting it is required specifically for Jaeger), explains operation_name as a filter, and gives ISO 8601 as the time format. This meaningfully exceeds the bare schema.

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 ('Get performance statistics for a service or operation'), which is clear and distinct from trace-retrieval siblings. However, it does not explicitly contrast itself with siblings like search_traces or get_slow_traces, leaving the agent to infer the boundary.

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 gives no when-to-use guidance, no prerequisites, and no mention of alternatives despite six sibling tools that overlap in domain (find_errors, get_slow_traces, search_traces). The agent must guess when aggregate stats are preferable to raw traces.

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