get_hierarchyWalk the full taxonomic hierarchy (lineage) for a TSN from ITIS — kingdom down to the taxon and its children. Returns each rank with its tsn, name, rank, and parent_tsn. Pass a TSN from search_taxa. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| tsn | Yes | Taxonomic Serial Number, e.g. 180582. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "tsn": 180582
+ },
+ {
+ "tsn": "183654"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate the tool is read-only, non-destructive, and idempotent. The description adds that it returns each rank with tsn, name, rank, and parent_tsn, and mentions it is keyless. This transparently describes the output and access requirements.
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 concise: three sentences covering purpose, return data, and prerequisites/cost. Every sentence adds value without unnecessary detail.
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?
Given the tool's simplicity (1 parameter, no output schema), the description covers the main aspects: purpose, output structure, and usage context. Lacks error handling details, but overall sufficiently complete.
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?
The schema has 100% coverage for the single parameter tsn, describing it as 'Taxonomic Serial Number, e.g. 180582.' The description adds value by stating the TSN should come from search_taxa, providing additional context beyond the schema.
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 states the tool walks the full taxonomic hierarchy from kingdom down to the taxon and its children for a given TSN. This distinguishes it from sibling tools like search_taxa and get_common_names, which serve different purposes.
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 specifies that the TSN should come from search_taxa and that the tool is keyless (free). While it doesn't explicitly state when not to use it, the context of sibling tools and the explicit prerequisite provide good usage guidance.
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 occupy overlapping roles: ask_pipeworx and ask_pipeworx_beta are currently identical, ask_pipeworx_grounded/deep_research/validate_claim all provide grounded answering, and bet_research/polymarket_edges/polymarket_arbitrage all surface betting opportunities. The descriptions are detailed, but the boundaries between routers and research modes are fuzzy enough that an agent could easily select the wrong one. The taxonomy, memory, and subscription clusters are distinct, but they are drowned out by the overlapping meta-tools.
All names use snake_case, which provides some visual consistency, but the verb_noun pattern is not consistently applied: search_taxa/get_hierarchy are clean verb_noun, while deep_research, entity_profile, polymarket_edges, and bet_research are noun-ish or reversed patterns. There is good family-level consistency within ask_pipeworx_* and polymarket_*, but the overall set mixes conventions and requires reading descriptions to infer what each tool does.
34 tools is well over the 25-tool threshold and reflects a sprawling multi-domain server spanning taxonomy, structured-data lookup, prediction markets, subscriptions, memory, and AI visibility. Each cluster may be individually reasonable, but as a single MCP surface it is too heavy and forces agents to filter through many irrelevant tools.
For the broad data-research and prediction-market purpose, the surface is fairly complete: it covers routing, grounded answers, deep multi-source research, entity profiles, comparisons, claim validation, entity resolution, subscriptions, alerts, memory, and market edge/fill checks. Minor gaps exist—no direct web-search tool, the beta router adds no current behavior, and some patent endpoints soft-fail—but agents can generally work around them.