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extract_yc

Read-only

Scrape YC company listings from a ycombinator.com/companies search URL. Returns name, batch, status, tags, and description per company. Freshness is unknown — YC listings carry no reliable per-company update date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYC URL e.g. https://www.ycombinator.com/companies?query=mcp

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

The description adds a meaningful behavioral caveat about data freshness ('Freshness is unknown') which goes beyond the readOnlyHint and openWorldHint annotations. It does not disclose potential scraping limitations or rate limits, but the freshness note is valuable context for an open-world data source.

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 two sentences, front-loaded with the action, and includes the key return fields and a caveat without any wasted words. It is well-structured and easy to parse.

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?

Without an output schema, the description meaningfully lists the per-company data returned (name, batch, status, tags, description) and notes the freshness caveat. For a single-parameter scraping tool, this is sufficient context.

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 parameter 'url' already has a full description in the schema with an example, and the description's reference to 'ycombinator.com/companies search URL' aligns with that. With 100% schema coverage, the description adds no extra parameter-level meaning 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?

The description clearly states the specific action (scrape YC company listings) and the source URL type, distinguishing it from sibling extract_* tools. It also lists the exact data fields returned, leaving no ambiguity about the tool's function.

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

Usage Guidelines3/5

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

The description implies the tool is for scraping YC company listings but does not explicitly state when to use it over alternatives or provide exclusions. There is no mention of prerequisites or use cases where another tool would be more appropriate.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct data source (finance, GitHub, Hacker News, etc.), with clear separation and no overlap. An agent can easily distinguish which tool to use for a given source.

Naming Consistency4/5

Tools use a consistent verb_noun pattern with 'extract_' for data extraction and 'search_' for search functions. The outlier 'package_trends' is still descriptive and fits the theme, so the pattern is mostly predictable.

Tool Count5/5

11 tools is well-scoped for a data aggregation server. Each tool serves a clear purpose and the count is neither too sparse nor overwhelming.

Completeness4/5

The server covers a broad range of sources (finance, code, news, social, academia, jobs, packages). Minor gaps like missing Twitter or general news are acceptable given the breadth already provided.