otel-mcp

send_metric

Transmit OpenTelemetry metrics to OTLP endpoints for monitoring and observability. Define metric instruments with name, kind, unit, and data points to track system performance.

Instructions

Send one or more metric instruments.

Each metric dict accepts: name, kind (counter/up_down_counter/gauge/ histogram), unit, description, points (list of {value, attributes}). For histograms, value may be a list of samples.

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": {
      "service_name": "<service_name>",
      "metrics": "<metrics>"
    },
    "name": "send_metric"
  }
}

Input Schema

Name	Required	Description	Default
`service_name`	Yes
`metrics`	Yes
`resource_attributes`	No
`endpoints`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 21, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the structure of metric data but doesn't mention whether this is a read/write operation, what permissions are needed, whether it's idempotent, or what happens on failure. The description adds some context about metric structure but lacks critical behavioral traits.

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?

The description is efficiently structured with a clear purpose statement followed by specific details about the metrics parameter. Every sentence adds value without redundancy, making it appropriately sized and front-loaded.

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?

Given 4 parameters with 0% schema coverage and no annotations, the description provides good detail about the 'metrics' parameter but leaves others unexplained. The existence of an output schema reduces the need to describe return values, but the description could better address the tool's overall context and behavioral aspects.

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?

With 0% schema description coverage, the description compensates well by detailing the structure of the 'metrics' parameter, including accepted fields like 'name', 'kind', 'unit', 'description', and 'points'. However, it doesn't explain the other 3 parameters (service_name, resource_attributes, endpoints), leaving them undocumented.

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 clearly states the tool's purpose: 'Send one or more metric instruments.' It specifies the action (send) and resource (metric instruments), but doesn't differentiate from sibling tools like 'send_log' or 'send_trace' beyond mentioning metrics specifically.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools like 'send_log' or 'send_trace', nor does it provide context about appropriate use cases or prerequisites for sending 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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