PyScrappy

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List Available Scrapers

list_available_scrapers

List all scraper identifiers registered on the server to find valid names before scraping. Returns an array of scraper names for use with scrape_with.

Instructions

List every scraper registered with this server and return their names for use with scrape_with.

Reads the server's in-process scraper registry, which includes built-in scrapers plus any installed third-party pyscrappy-* plugin packages that self-register on import. No network or browser access is performed and no state is changed. If no scrapers are registered, returns an empty list.

Returns: list[str]: Scraper name identifiers (for example ["amazon", "flipkart", "youtube"]), each usable as the scraper argument to scrape_with. Empty list when none are registered.

Usage Guidelines: Call this first to discover valid scraper names, then pass a returned name to scrape_with; use it to confirm a plugin registered correctly after installing a pyscrappy-* package.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv1.3.3Jul 31, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```
- removedInput schema / title
```
Removed value: -"list_available_scrapersArguments"
```
- removedOutput schema / title
```
Removed value: -"list_available_scrapersDictOutput"
```
Addedv1.3.0Jul 28, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that no network or browser access is performed, no state is changed, and that the tool reads an in-process registry. It also covers the empty-list edge case and plugin self-registration behavior.

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?

The description is well-structured with a purpose statement, behavioral details, return format, and usage guidelines. It is slightly redundant (e.g., empty list behavior appears twice, and the connection to scrape_with is stated more than once), but remains focused and front-loaded.

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 simplicity (zero parameters, output schema available), the description is fully complete. It explains what values are returned, how they should be used, what happens when no scrapers exist, and what side effects (none) to expect.

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

Parameters4/5

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

The tool has zero parameters, so there is no parameter semantics to add beyond the schema. The description still confirms the absence of parameters by describing the tool as a simple registry listing, and it clearly explains what the returned values mean.

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 uses a specific verb and resource ('List every scraper registered with this server') and states the results are for use with scrape_with. This clearly distinguishes it from sibling scraping tools like scrape_url and scrape_with, which actually perform scrapes.

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 instructs the agent to call this first to discover valid scraper names and then pass a returned name to scrape_with. It also gives a concrete verification use case (confirming a plugin registered), leaving no doubt about when and how to use the tool.

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