PyScrappy

Overview Schema Related Servers Score Discussions

search_linkedin_jobs

Find LinkedIn job postings by keyword and location, returning matched jobs with title, company, location, URL, and posting date from public search results.

Instructions

Search LinkedIn public job postings and return a list of matched jobs.

Scrapes LinkedIn's public job search results over the network (no login required) and returns a list of dicts, one per posting, typically with keys: title, company, location, url, and posted_date. Returns an empty list if no postings match or the query yields no results. Live web scraping, so results reflect LinkedIn at call time and may vary between runs.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	Yes	Job title or keywords as a string. Example: "machine learning engineer". No default (required).
`location`	No	Location filter as a string; city, region, or country. Example: "London" or "United Kingdom". No default (required).
`max_pages`	No	Number of result pages to scrape, as an integer. Each extra page adds jobs but more scraping time. Example: 2. Default: 1.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`count`	No
`errors`	No
`scraper`	No
`source_urls`	No

Schema Changelog

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

Changed3 schema fields changedJul 31, 2026

changedInput schema / properties / location / description

Previous value: -"Location filter, e.g. \"London\" or \"United Kingdom\"."New value: +"Location filter as a string; city, region, or country. Example: \"London\" or \"United Kingdom\". No default (required)."

changedInput schema / properties / max_pages / description

Previous value: -"Pages of results to scrape (default 1)."New value: +"Number of result pages to scrape, as an integer. Each extra page adds jobs but more scraping time. Example: 2. Default: 1."

changedInput schema / properties / query / description

Previous value: -"Job title or keywords, e.g. \"machine learning engineer\"."New value: +"Job title or keywords as a string. Example: \"machine learning engineer\". No default (required)."

Changed20 schema fields changedv1.3.3Jul 31, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

addedInput schema / properties / location / description

Added value: +"Location filter, e.g. \"London\" or \"United Kingdom\"."

removedInput schema / properties / location / title
```
Removed value: -"Location"
```

addedInput schema / properties / max_pages / description

Added value: +"Pages of results to scrape (default 1)."

removedInput schema / properties / max_pages / title
```
Removed value: -"Max Pages"
```

addedInput schema / properties / query / description

Added value: +"Job title or keywords, e.g. \"machine learning engineer\"."

removedInput schema / properties / query / title
```
Removed value: -"Query"
```

removedInput schema / title

Removed value: -"search_linkedin_jobsArguments"

removedOutput schema / $defs

Removed value: -{
-  "ToolError": {
-    "description": "A non-fatal problem encountered while scraping.",
-    "properties": {
-      "message": {
-        "title": "Message",
-        "type": "string"
-      },
-      "url": {
-        "title": "Url",
-        "type": "string"
-      }
-    },
-    "required": [
-      "url",
-      "message"
-    ],
-    "title": "ToolError",
-    "type": "object"
-  }
-}

removedOutput schema / properties / count / title
```
Removed value: -"Count"
```
removedOutput schema / properties / data / title
```
Removed value: -"Data"
```
removedOutput schema / properties / errors / items / $ref
```
Removed value: -"#/$defs/ToolError"
```

addedOutput schema / properties / errors / items / description

Added value: +"A non-fatal problem encountered while scraping."

addedOutput schema / properties / errors / items / properties

Added value: +{
+  "message": {
+    "type": "string"
+  },
+  "url": {
+    "type": "string"
+  }
+}

addedOutput schema / properties / errors / items / required
```
Added value: +[
+  "url",
+  "message"
+]
```
addedOutput schema / properties / errors / items / type
```
Added value: +"object"
```
removedOutput schema / properties / errors / title
```
Removed value: -"Errors"
```
removedOutput schema / properties / scraper / title
```
Removed value: -"Scraper"
```
removedOutput schema / properties / source_urls / title
```
Removed value: -"Source Urls"
```
removedOutput schema / title
```
Removed value: -"ScrapeToolResult"
```

Addedv1.2.0Jul 26, 2026
Removedv1.2.0Jul 26, 2026
AddedJul 26, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it reveals that the tool scrapes over the network (not an API), requires no login, returns a list of dicts with typical keys, returns an empty list on no matches, and that results are live and may vary between runs. This is strong transparency. It doesn't mention rate limits or error handling, but the disclosed traits are sufficient for a 4.

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 compact and front-loaded. The first sentence states the purpose, and the second block adds essential behavioral details (no login, return format, empty-list behavior, live scraping variability). Every sentence earns its place with no fluff or repetition.

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?

Given the tool's scraping nature and the presence of a rich output schema, the description is complete. It covers purpose, network method, auth requirements, output structure, empty-result behavior, and data freshness. This is sufficient for an agent to decide when and how to invoke the tool without needing additional information.

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 schema description coverage is 100% — every parameter (query, location, max_pages) has a clear description with examples and defaults. The tool description adds no extra parameter semantics beyond what the schema already provides, so the baseline of 3 is appropriate. No additional value is contributed.

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's function: 'Search LinkedIn public job postings and return a list of matched jobs.' It specifies the resource (LinkedIn job postings), the verb (search), and the output (list of matched jobs). This distinguishes it from sibling search tools that target other sources like GitHub, Hacker News, or books.

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

Usage Guidelines4/5

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

The description provides context on when to use the tool: for scraping LinkedIn's public job search without login. It mentions network scraping and live results. However, it does not explicitly exclude alternatives or state "use this instead of X" — although sibling tools are all different sources, making the context fairly clear. The lack of explicit exclusions keeps it from a 5.

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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