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Glama

openalex

by io.github.pipeworx-io

Get Scholarly Work

get_scholarly_work
Read-onlyIdempotent

Fetch a single scholarly work from OpenAlex by its OpenAlex ID (e.g. "W2741809807") or DOI (e.g. "10.1038/s41586-021-03819-2"). Returns the full record + reconstructed abstract and the works it CITES (referenced_works) — for backward citation-graph navigation. Use after search_works, or whenever you have a DOI/ID. (Named get_scholarly_work to avoid colliding with Crossref get_work.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesOpenAlex work ID ("W...") or a DOI ("10.xxxx/yyyy" or a full doi.org URL).
_apiKeyNoOpenAlex API key. Optional — Pipeworx supplies one; pass your own to bill your account instead.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / properties / _apiKey
      Added value: +{
+  "description": "OpenAlex API key. Optional — Pipeworx supplies one; pass your own to bill your account instead.",
+  "type": "string"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": "W2741809807"
+  },
+  {
+    "id": "10.1038/s41586-021-03819-2"
+  }
+]
  3. Changed1 schema field changed
    • removedInput schema / properties / citing_limit
      Removed value: -{
-  "description": "How many top (most-cited) citing works to include (0-25, default 5).",
-  "type": "number"
-}
  4. Added

TDQS

A4.5/5.0
Behavior4/5

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 known. The description adds useful behavioral context: it returns the full record, reconstructed abstract, and cited works (referenced_works), which is beyond a simple fetch. It also notes that it supports ID or DOI formats, giving the agent concrete expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the core action, then return details, then usage context. The parenthetical naming rationale is a small but useful note that prevents confusion with another tool. No redundant phrasing or filler exists.

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?

Despite no output schema, the description states exactly what is returned (full record, abstract, referenced_works), which is sufficient for this simple fetch tool. Combined with annotations and a clear usage context, the description covers all necessary information for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for both parameters (id and _apiKey), so the schema already documents the parameter meanings. The description adds example values for id (e.g., 'W2741809807' and '10.1038/s41586-021-03819-2') but these are also present in the schema's examples. Therefore, the description adds minimal extra semantic value beyond what the schema provides.

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?

The description clearly states the tool fetches a single scholarly work from OpenAlex by OpenAlex ID or DOI, which is a specific verb+resource+method. It distinguishes itself from sibling tools like search_works by explicitly saying it fetches a single work rather than searching. The inclusion of example IDs further clarifies the exact resource.

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

Usage Guidelines5/5

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

The description explicitly says 'Use after search_works, or whenever you have a DOI/ID', giving clear when-to-use guidance. It also mentions the purpose for backward citation-graph navigation, which helps the agent decide between this and alternative lookups. While it doesn't explicitly list when-not-to-use alternatives, the guidance is clear enough for a single-record fetch tool.

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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TDQS

A3.5/5.0
Disambiguation1/5

Several tools are effectively indistinguishable or near-duplicates: ask_pipeworx_beta is explicitly an identical copy of ask_pipeworx with no active experimental changes, and ask_pipeworx_grounded is a variant of the same router. discover_tools, suggest_questions, deep_research, and the ask_pipeworx family also heavily overlap as discovery/answer surfaces, while bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_fill_risk create a dense prediction-market cluster with fuzzy boundaries.

Naming Consistency3/5

Everything is snake_case and many names follow a readable verb_noun pattern (search_works, resolve_entity, validate_claim, suggest_questions), but conventions are mixed: noun-first domain-prefixed names (polymarket_edges, pipeworx_feedback, pipeworx_trending), bare verbs (remember, forget, recall), and adjective_noun names (deep_research, recent_changes) coexist. The inconsistency is not chaotic, but it is not a unified scheme.

Tool Count2/5

36 tools is well over the 25-tool threshold for a heavy toolset, and the count is inflated by many tangential concerns: memory, subscriptions, feedback, trending, npm dependency scanning, AI visibility, and llms.txt generation. Only a small subset actually serves the stated OpenAlex/scholarly purpose, so the size feels bloated rather than well-scoped.

Completeness2/5

For a server named openalex, the scholarly surface is incomplete: works support search and fetch, but authors and institutions only support search with no get-by-ID, concepts support get but no search, and major OpenAlex resource types like sources, publishers, funders, and topics are absent. The many non-OpenAlex tools do not fill these gaps and instead dilute the domain coverage.

Resources