get_package_scoreGet the pub.dev quality score for a Dart/Flutter package: granted/max pub points, like count, popularity, 30-day download count, and classification tags (platforms, SDKs, license).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | pub.dev package name, e.g. "http". |
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?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds useful detail about what data the tool reports, but it does not disclose behavioral aspects such as whether it queries live pub.dev data, possible latency, or how missing packages are handled. This stays at the calibrated baseline for annotation-covered read tools.
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 a single, front-loaded sentence that immediately identifies the tool's purpose and then lists the returned data components. Every part adds useful information without repetition or filler.
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 one-parameter read-only tool with no output schema, the description is largely complete: it identifies the input and describes the main output categories. It could go slightly further by noting behavior for invalid or nonexistent package names, but such an edge case is minor given the openWorldHint and the simplicity of the tool.
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 the 'name' parameter already explained and given an example. The description reinforces that the package is a Dart/Flutter pub.dev package, but it does not add materially new parameter semantics beyond the schema, so the baseline score of 3 is appropriate.
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 states a specific action ('Get') and a specific resource ('the pub.dev quality score for a Dart/Flutter package'), and then enumerates concrete components of that score. This distinguishes it well from nearby siblings like get_package or search_packages, which target package metadata or discovery rather than scoring.
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 gives clear context for when the tool is appropriate: whenever the agent needs a package's pub.dev quality score and its component metrics. It does not explicitly mention alternatives or exclusion conditions, but its specificity makes the use case obvious and effectively routes around search or metadata tools.
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.
Several tools have clear functional boundaries, but there is meaningful overlap at the top level: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share one routing pipeline, and ask_pipeworx_beta is currently identical to ask_pipeworx. The six polymarket_* tools also form a dense family where an agent must read long descriptions to distinguish arbitrage scanning from edge detection from fill-risk evaluation.
Names are uniformly lowercase snake_case and mostly follow verb_noun or domain-prefix conventions, which makes the set much more predictable than its count suggests. Minor deviations exist: ask_pipeworx variants are product-noun phrases, polymarket_edges is a noun phrase rather than a verb-led tool, and pairs like polymarket_edges vs polymarket_edge_tracker are easy to misread.
With 31 tools, this server is above the 25+ threshold and feels overloaded for a single MCP surface. It mixes broad data research, prediction-market analysis, memory, subscriptions, feedback, and niche utilities like generate_llms_txt, so the set is more like several related servers merged together.
The core workflow is well covered: discovery, single-answer routing, grounded verification, deep research, entity resolution, comparison, change tracking, subscription lifecycle, and even memory primitives. Missing are minor lifecycle refinements such as updating an existing subscription, and the number of overlapping entry points makes it slightly harder to guarantee the agent will always choose the intended path.