mcp-knowledge

competitor_pricing_scrape

Read-only

Scrape and parse a competitor pricing page from a URL or domain. Fetches via proxy-aware timedFetch (tries /pricing, /plans, homepage fallback), then extracts: plan names, prices, billing cadence (monthly/annual/usage-based/one-time), key features, free tier presence, enterprise tier, estimated price range. Returns structured pricing tiers. If unfetchable or no pricing found (anti-bot, SPA, auth wall): returns a clear degraded result with warnings and signals — never fake success. ICP: founders, product managers, pricing strategists, competitive intel teams. Proxy-aware (AICI_RESEARCH_PROXY_URL). Cache TTL 6h.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes	Competitor URL or domain (e.g. 'https://notion.so/pricing', 'notion.so', 'https://www.example.com'). For best results, provide the direct pricing page URL.
`async`	No	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`tiers`	Yes
`domain`	Yes
`status`	Yes
`warnings`	Yes
`url_fetched`	Yes
`has_free_tier`	Yes
`pricing_found`	Yes
`quality_score`	Yes
`raw_price_signals`	Yes
`has_enterprise_tier`	Yes
`plan_names_detected`	Yes
`billing_model_signals`	Yes
`estimated_price_range`	Yes

TDQS

A4.5/5.0

Behavior5/5

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

The description explains the proxy-aware fetching, fallback behavior ('tries /pricing, /plans, homepage fallback'), failure handling (clear degraded result with warnings), caching (TTL 6h), and async support. This adds significant behavioral context beyond the annotations (readOnlyHint, openWorldHint). No contradiction.

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 fairly concise but contains several details (e.g., ICP list, tech specifics) that could be slightly trimmed. It is front-loaded with the purpose and structured well, but not maximally concise.

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 complexity (web scraping with fallback, failure handling, caching), the description covers all essential aspects: method, output, failure behavior, ICP, and technical parameters like proxy and cache. The existence of an output schema compensates for not detailing return format, so it's complete.

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

Parameters5/5

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

Both parameters are described in the schema, and the description adds extra guidance: for 'url' it recommends providing the direct pricing page, and for 'async' it explains the job result polling mechanism. This enriches the schema descriptions.

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?

The description clearly states the tool scrapes and parses competitor pricing pages from a URL, with specific extracted data. It does not explicitly differentiate from sibling tools like 'competitor_pricing_radar', so it loses one point for lack of distinction.

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 identifies the ICP (founders, product managers, etc.) and advises providing the direct pricing URL. It does not specify when to avoid using this tool or mention alternatives, so it's clear but not exhaustive.

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

C2.8/5.0

Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

competitor_pricing_scrape

Input Schema

Output Schema

TDQS

Glama MCP Gateway

TDQS

Resources