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ApexMCP

ApexMCP

by mad-science-lab
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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apex_probe_history

Retrieve historical probe readings from an Apex controller log, defaulting to Temp and pH, downsampled to a max point count for monitoring and trend analysis.

Instructions

Probe history from the controller's log (default Temp and pH), downsampled to max_points.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "apex_probe_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNo
probesNo
max_pointsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, but it does disclose two useful traits: the data source is the controller's log and results are downsampled to max_points. It omits what happens when a requested probe doesn't exist, how gaps in the log are handled, and whether the default time window is a rolling 24 hours.

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?

A single compact sentence with no filler, and the core resource is front-loaded. It is arguably too terse rather than bloated, so conciseness is a strength here.

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, but the description still leaves the days parameter, probe-name format, and edge-case behavior unaddressed. For a 3-parameter time-series query with zero annotation coverage, this is only minimally adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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. It explains max_points (downsampling cap) and implies the probes parameter via 'default Temp and pH', but the days parameter — the primary scope control — is never mentioned, leaving a third of the input undocumented anywhere.

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 states a specific verb+resource: retrieving probe history from the controller's log. It implicitly distinguishes itself from siblings like apex_get_probes (current probes) and apex_probe_stats (statistics) via the word 'history', but never names or contrasts those siblings explicitly.

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 on when to use this tool versus apex_probe_stats or apex_get_probes, and no stated preconditions (e.g., controller reachable, log retention limits). Usage must be inferred from the name alone.

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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