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ai-integr8tor

Tavily MCP Server

tavily_extract

Extract raw content from web pages in markdown or text format. Supports advanced extraction for complex sites like LinkedIn.

Instructions

Extract content from URLs. Returns raw page content in markdown or text format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesList of URLs to extract content from
queryNoQuery to rerank content chunks by relevance
formatNoOutput formatmarkdown
extract_depthNoUse 'advanced' for LinkedIn, protected sites, or tables/embedded contentbasic
include_imagesNoInclude images from pages
include_faviconNoInclude favicon URLs
Behavior2/5

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

With no annotations, the description carries full burden but only states the basic outcome (returns raw content). It does not disclose rate limits, authentication needs, or handling of dynamic content, which are important for agent decision-making.

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 a single sentence that efficiently conveys the tool's core function. While concise, it could be more structured or include a brief note on key features without adding verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters and no output schema, the description is too minimal. It does not mention optional parameters like query, format, depth, or include images, leaving the agent with incomplete context about the tool's capabilities.

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 input schema has 100% coverage with descriptions for all 6 parameters, so the baseline is 3. The tool description adds no additional parameter-level meaning beyond what the schema already provides.

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 extracts content from URLs and returns it in markdown or text format. However, it does not explicitly differentiate from sibling tools like search or crawl, so it lacks sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as tavily_search or tavily_crawl. It only states what it does, leaving the agent to infer usage context.

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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