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Oxylabs Web API MCP Server

Oxylabs Web API MCP Server

by thevastas
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Check a render job

check_scrape
Read-only

Poll a JavaScript-rendering job started by scrape or extract to retrieve its finished result. Use the job_id to check status and get full output when rendering completes.

Instructions

Check a JavaScript-rendering job started by scrape or extract.

While it says running, poll again in ~10 seconds — and do other work between polls. A render runs 30-150s, so a dozen polls are normal and a job still running at 100s is not stuck. The finished result is returned in full.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "check_scrape"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesThe `job_id` returned by a `run_js` call.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare readOnlyHint and openWorldHint, so the description carries the polling/latency story and does it well, including the 'a job still running at 100s is not stuck' reassurance and the completeness of the finished result. It stops short of describing failure or timeout states, which would matter for a long-running async job.

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?

Three short sentences, front-loaded with the purpose before the operational guidance. Every sentence carries distinct information (what it checks, poll cadence, expected duration band) with no filler.

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?

For an async job-status tool with an output schema, the description covers the poll loop, timing expectations, and result completeness, which is what an agent needs to call it correctly. Missing only edge-case behavior such as failed or expired jobs.

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?

There is only one parameter and schema description coverage is 100%, so the schema already fully documents job_id. The description adds no format, source, or syntax detail beyond the schema, making the baseline 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Check a JavaScript-rendering job') and names the tools that create such jobs (`scrape`, `extract`), which helps separate it from sibling operations like search and read_scraped. The only wrinkle is that the input schema attributes job_id to a `run_js` call, which does not appear in the sibling list, slightly muddying which upstream tool it complements.

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?

Gives explicit operational guidance: poll again in ~10 seconds while status is 'running', do other work between polls, and no need to fetch results elsewhere because the finished result is returned in full. It also bounds normal job duration (30-150s) so the agent knows when polling is still expected rather than pathological.

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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