Autonomous SRE & Distributed Incident Diagnosis MCP Server

fetch_error_traces

Retrieve structured OpenTelemetry error traces for a microservice, including trace IDs, span IDs, HTTP status codes, error messages, and stack traces to diagnose incidents.

Instructions

Fetch structured OpenTelemetry error traces including traceId, spanId, HTTP status codes, error messages, and stack traces.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "serviceName": "<serviceName>"
    },
    "name": "fetch_error_traces"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Maximum number of trace spans to return (default 10)
`serviceName`	Yes	The target microservice name (e.g. "order-service", "payment-gateway")
`minStatusCode`	No	Minimum HTTP status code threshold (e.g. 500 for server errors)
`timeframeMinutes`	No	Lookback timeframe in minutes (default 30)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 11, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the full burden of behavioral disclosure. It does state the return contents, which is useful, but says nothing about read-only semantics, pagination/limit behavior, auth requirements, or whether an empty result is possible within the lookback window.

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?

A single tightly written sentence with the resource stated first and the payload details after. There is no filler, hedging, or redundant restatement of the tool name.

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 four-parameter read tool with full schema coverage, the definition covers what the tool returns and what it operates on, which partly compensates for the absent output schema. Only the behavioral edge cases (empty results, limits/truncation) are left unaddressed.

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 all four parameters (serviceName, limit, minStatusCode, timeframeMinutes) are already documented with examples and defaults. The description adds no parameter-level meaning beyond the schema, which is the baseline 3 when the schema does the heavy lifting.

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?

The description names a specific verb and resource ("Fetch structured OpenTelemetry error traces") and enumerates the payload contents (traceId, spanId, HTTP status, error messages, stack traces). It does not explicitly differentiate itself from siblings like query_service_metrics, but the resource is distinct enough that the boundary is inferable.

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?

No explicit when-to-use statement, no prerequisites, and no named alternatives. Usage is only implied by the phrase "error traces," which suggests debugging/failure investigation rather than metrics or incident summarization; the agent must infer that routing itself.

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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