Pick the BEST version from a comma-separated list that satisfies a range — the highest satisfying version (upgrade target). Correctly excludes inapplicable prereleases (npm rules) and rejects invalid list entries. Returns the max satisfying version or "none".
| Name | Required | Description | Default |
|---|---|---|---|
| range | Yes | npm-style range, e.g. "^1.0.0" | |
| versions | Yes | Comma-separated version list, e.g. "1.4.1, 1.5.0-beta.1, 1.6.0" |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden and does so well. It discloses npm prerelease exclusion rules, rejection of invalid list entries, and the exact return value ('none' when no match). These are meaningful behavioral traits beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded with the core purpose, and every sentence adds value. It avoids restating the tool name and packs key behaviors and return semantics into three tight sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter pure function with no output schema, the description fully covers inputs, behavior, validation rules, and return value. The tool is complete enough for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters documented by example. The description reinforces that versions are comma-separated and range is npm-style, but adds little beyond the schema. Baseline 3 is appropriate because the schema already handles parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the specific operation: pick the highest version satisfying a range from a comma-separated list. It distinguishes itself from the sibling semver tools by emphasizing 'max satisfying version' as an upgrade target.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool: when you need the best/highest satisfying version, such as an upgrade target. It does not explicitly name alternatives or state when not to use it, but the purpose is distinct enough from semver_satisfies, semver_compare, and semver_bump that the usage context is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation—encoding, color conversion, parsing, hashing, JWT validation, Markdown rendering, regex testing, SemVer operations, diffing, URL analysis, and UUID generation. The four SemVer tools are related but cleanly separated by action (bump vs compare vs max vs satisfies), and descriptions clarify their boundaries.
Tools overwhelmingly follow an object_verb snake_case convention (base64_encode, csv_parse, regex_test, semver_bump). Semver_max and semver_satisfies deviate slightly from the imperative verb pattern, but the overall naming is predictable and searchable.
At 16 tools, the server is slightly above the ideal 3–15 tool range but each utility earns its place for a general-purpose developer toolbox. No tools feel redundant, and the count remains manageable because the names and domains are highly scannable.
The toolkit covers a solid breadth of common developer utilities: encodings, common formats (JSON, CSV, Markdown), hashing/JWT, regex, SemVer, cron, URL, UUIDs, and diffing. It lacks some fringe converters such as YAML/XML parsing or HTML escape/unescape, but these are minor gaps that agents can work around rather than dead ends.