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get_server_info

Check the running server version, changelog, release history, and data freshness to verify whether local Graph Atlas data is current.

Instructions

About this server — running version, its changelog entry, data freshness (latest snapshots and newest detected changes), and how releases work: the snapshot DATABASE is re-released daily as calendar-tagged GitHub releases (e.g. v2026.08.07) when changes are detected, while the SERVER code ships on npm with semver versions (e.g. v0.1.0). Call for "what version is this?", "what's new in the latest Graph Atlas release?", or to check whether the local data is current.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.10.23
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the burden, and it does well: it clarifies that there are two distinct version streams (daily calendar-tagged GitHub snapshot releases vs. npm semver server releases), which prevents misreading the output, and frames the call as a freshness check. It never explicitly states the call is read-only side-effect free, which keeps it off a 5.

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 payload is front-loaded — the resource statement comes first, then the freshness detail, then the versioning scheme, then use cases. It is on the long side and the release-mechanics sentence is dense, but it earns its place by disambiguating the two version formats shown in the output.

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?

There is no output schema, and the description compensates fully: it lists the returned fields (version, changelog entry, latest snapshots, newest detected changes) and explains why two different version numbers may appear. An agent has everything needed to call and interpret this no-parameter tool.

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 zero parameters, so the baseline of 4 applies. The description correctly implies no input is needed and focuses entirely on what the call yields.

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?

Names a specific resource and enumerates exactly what it returns: running version, changelog entry, data freshness (latest snapshots and newest detected changes), and release mechanics. None of the sibling tools (search_changes, get_node_timeline, get_object_history, etc.) overlap with server metadata, so an agent can route to it unambiguously.

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?

Gives three concrete triggering questions in quotes ("what version is this?", "what's new in the latest Graph Atlas release?", "is the local data current?"), which is strong positive guidance. It does not name an alternative or an exclusion, but no sibling plausibly competes for these queries, 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.