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io.github.qso-graph/pota-mcp

io.github.qso-graph/pota-mcp

by qso-graph
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Get Version Info

get_version_info
Read-onlyIdempotent

Retrieve the running pota-mcp service version and current POTA API spec revision to compare deployments and detect version drift across MCP servers.

Instructions

Get pota-mcp service version and upstream spec version.

Returns the running PyPI version of pota-mcp and the POTA API revision currently in use. Use this to confirm fleet alignment across MCP deployments — agents can compare service_version and spec_version across servers to detect drift without going outside the MCP protocol.

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": "get_version_info"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description adds context on top: it returns the running PyPI version plus the POTA API revision in use, and can be compared across servers. It does not discuss failure modes, but for a zero-parameter version readout little else is needed.

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-loaded with the core statement, then the rationale. Mostly economical, though "detect drift without going outside the MCP protocol" is slightly padded relative to the informational content.

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

Completeness5/5

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

With zero parameters, rich annotations, and an output schema present, the description covers what the tool returns and why an agent would call it. Nothing needed for correct invocation is missing.

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?

The tool takes no parameters, so the baseline is 4. The description names the response fields (service_version, spec_version), which is a small bonus beyond the empty schema without being parameter semantics per se.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Get pota-mcp service version and upstream spec version") and immediately enumerates the two returned fields, service_version and spec_version. This is clearly distinguishable from all siblings, which are POTA park/user data tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Use this to confirm fleet alignment across MCP deployments" gives an explicit when-to-use condition (cross-server drift detection). No exclusions or named alternatives are given, but no sibling plausibly substitutes for this tool, so the gap is minor.

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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