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scholar-mcp

scholar-mcp

by pvliesdonk

Get Job Result

get_job_result
Read-only

Retrieve the status and result of a background job started by a long-running tool, returning output or an error when finished. Fetch promptly because job records expire.

Instructions

Get the status of a background job started by a long-running tool on this server; returns status (working, completed or failed) with the result or error once it finishes. Job records expire, so fetch a finished job's result promptly. Scholar MCP promotes slow work to a background job. PDF download and docling conversion usually take 1-5 minutes, a busy EPO traffic light is waited out, citation formatting enriches one paper after another, and graph traversal makes one rate-limited request per node. Semantic Scholar throttling defers the same work immediately and adds a reason to the handle. Those calls commonly answer with a job_id rather than a result; a cache hit answers inline, with no job.

Input Schema

NameRequiredDescriptionDefault
job_idYesThe job_id a long-running tool returned when it continued in the background.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.1.1
    • addedInput schema / properties / job_id / description
      Added value: +"The job_id a long-running tool returned when it continued\nin the background."
  2. Addedv1.10.0

TDQS

A4.5/5.0
Behavior5/5

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

Adds material behavior beyond the readOnly/non-destructive/idempotent annotations: job records expire so results must be fetched promptly, status is tri-state, results can come back as either a payload or an error, and throttling defers work with a reason attached to the handle. The expiry warning is exactly the kind of non-obvious constraint annotations cannot express.

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?

Front-loaded with the core purpose, status values, and the expiry caveat before the supporting detail. The middle sentence enumerating specific slow operations (docling conversion, EPO traffic light, graph traversal) is somewhat long-winded, but each item justifies why a job handle exists rather than a result.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and 100% parameter coverage, the description only needs to supply the operational context, and it does: triggering conditions, status semantics, expiry, and inline fallback. The only minor gap is no guidance on polling cadence or backoff while a job is still 'working'.

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?

The single job_id parameter is fully documented in the schema, and the description's framing ('a long-running tool returned when it continued in the background') largely restates it. The surrounding context about how job_id values originate from deferred or slow calls is mildly useful but does not add format or validation detail beyond the schema.

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?

States a specific verb and resource ('Get the status of a background job') and immediately enumerates the observable outcomes (working, completed or failed, with result or error). This is distinguishable from every sibling tool, which are all paper/author/standard lookups rather than job-handle polling.

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?

Explicitly frames when this tool is the right call ('Those calls commonly answer with a job_id rather than a result') and when it is not needed ('a cache hit answers inline, with no job'). It also enumerates which upstream operations produce job handles (PDF download, docling conversion, EPO traffic light, citation formatting, graph traversal, throttling), which lets an agent recognize the trigger conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.