Skip to main content
Glama

Cortex

by io.cortex.mcp
OverviewDiscussionsAdmin

Getcustommetricdata

getCustomMetricData

Retrieve custom metric data points for an entity. Returns paginated time-series data for a specific custom metric, with optional filtering by date range to analyze trends and patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYesPage number to return, 0-indexed. Default 0.
contextYes Explain why you're invoking this tool now and how its output will be used. Then state how this call supports your *overall objective* and fits into your broader plan across all tool calls (e.g., why this tool vs. others, and what step it unblocks). Never share any personal details or sensitive information.
endDateNoEnd date for the filter, inclusive (UTC, e.g. 2026-06-22T00:00:00)
tagOrIdYesEntity identifier - can be a tag or CID
pageSizeYesNumber of results to return per page, between 1 and 1000. Default 250.
startDateNoStart date for the filter, inclusive (UTC, e.g. 2026-06-22T00:00:00). Default: 6 months ago
session_idYesSession continuity handle, one of two values: the ses_ ID issued for the task underway, or start. This server cannot link your calls between requests on its own, so session continuity travels in this parameter instead. If you were handed a session_id for this task — for example by the agent that spawned you — send that exact value from your first call. Otherwise send start on your first call; the server will issue an opaque correlation ID in the mcp_session field of the result, or in a text block at the start of the result beginning [session_id issued. Then send that exact ses_ value on every later call and hand it to any subagents working the same task. start always begins a new, unrelated task — never send it mid-task. If you send a value this server does not recognize, the result reports it: mcp_session.status of unrecognized, or a text block beginning [session_id unrecognized; re-send the ID issued for this task, or start if none was issued yet. Never invent a ses_ value.
customMetricKeyYesKey for the custom metric filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedInput schema / properties / endDate / description
      Previous value: -"End date for the filter (inclusive)"New value: +"End date for the filter, inclusive (UTC, e.g. 2026-06-22T00:00:00)"
    • addedInput schema / properties / session_id
      Added value: +{
+  "description": "Session continuity handle, one of two values: the ses_ ID issued for the task underway, or start. This server cannot link your calls between requests on its own, so session continuity travels in this parameter instead. If you were handed a session_id for this task — for example by the agent that spawned you — send that exact value from your first call. Otherwise send start on your first call; the server will issue an opaque correlation ID in the mcp_session field of the result, or in a text block at the start of the result beginning [session_id issued. Then send that exact ses_ value on every later call and hand it to any subagents working the same task. start always begins a new, unrelated task — never send it mid-task. If you send a value this server does not recognize, the result reports it: mcp_session.status of unrecognized, or a text block beginning [session_id unrecognized; re-send the ID issued for this task, or start if none was issued yet. Never invent a ses_ value.",
+  "pattern": "^(start|ses_[0-9A-Za-z]{27})$",
+  "type": "string"
+}
    • changedInput schema / properties / startDate / description
      Previous value: -"Start date for the filter (inclusive). Default: 6 months"New value: +"Start date for the filter, inclusive (UTC, e.g. 2026-06-22T00:00:00). Default: 6 months ago"
    • changedInput schema / required
      Previous value: -[
-  "customMetricKey",
-  "tagOrId",
-  "pageSize",
-  "page",
-  "context"
-]New value: +[
+  "customMetricKey",
+  "tagOrId",
+  "pageSize",
+  "page",
+  "session_id",
+  "context"
+]
  2. First observed

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It does disclose two useful behavioral traits: the results are paginated and the data is time-series with optional date-range filtering. However, it does not explain how pagination behaves, the shape of each data point, sorting, or empty/error outcomes, leaving several behavioral aspects undisclosed.

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?

The description is a single sentence with the core purpose front-loaded. It has minimal waste, though 'custom metric data points' and 'time-series data for a specific custom metric' are slightly redundant. Overall it is concise and readable.

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

Completeness2/5

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

For a complex 8-parameter tool with no output schema and no annotations, the description is too thin. It doesn't describe the structure of the returned time-series data, the relationship between customMetricKey and tagOrId, or how the required context and session_id parameters factor in. It also fails to distinguish itself from the many closely-related sibling tools, leaving significant gaps.

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 the baseline of 3 applies. The description adds general context about pagination and date-range filtering, but it doesn't illuminate specific parameters beyond what the schema already provides. The schema already documents page/pageSize defaults, tagOrId as entity identifier, and customMetricKey as the metric filter key.

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 uses a specific verb and resource ('Retrieve custom metric data points for an entity') and adds distinguishing characteristics: paginated time-series data for a specific custom metric with optional date-range filtering. It does not explicitly name any sibling tool, but the 'custom metric' framing helps separate it from generic getCustomDataForEntity and similar tools.

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?

There is no guidance about when to use this tool versus alternatives such as getCustomDataForEntity, getCustomDataForEntityByKey, retrieveCustomDataForEntityAdvanced, or queryPointInTimeMetrics. The description never states exclusions or conditions, so an agent must infer the appropriate choice from name and schema alone.

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

All Cortex toolsInspect
Try in Browser
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources