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imshibaji

Headless Lead Scraping MCP Server

by imshibaji

Find Leads

find_leads

Find and verify business leads in priority order from Google Maps and web search engines, extract contact details, filter by required fields, and store them locally.

Instructions

Find leads in priority order: Google Maps places first (browser-rendered, incl. phone/website/address), then live web search engines, then related search engines. Crawls relevant pages, extracts and verifies leads with the LLM, deduplicates, filters by requiredFields, and stores them locally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
locationNo
requiredFieldsNo
maxSearchQueriesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
leadsYes
totalYes
Behavior4/5

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

With no annotations provided, the description takes on the full burden, and it delivers by outlining the process: browser-rendered Google Maps, crawling, LLM verification, deduplication, filtering, and local storage. It does not mention rate limits, authentication, or potential failure modes, so it is strong but not exhaustive.

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: the first front-loads the primary purpose and sources, and the second efficiently condenses the pipeline. Every sentence adds value with no redundancy.

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

Completeness3/5

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

The tool is complex – multi-source aggregation, crawling, extraction, filtering, storage – and the description provides a solid high-level overview. However, it leaves gaps such as how 'limit' interacts with the pipeline, what 'maxSearchQueries' controls, and the exact output shape (though an output schema exists). For an agent to invoke it correctly with parameters, more detail would be beneficial.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It only explains the 'requiredFields' param ('filters by requiredFields'), leaving 'limit', 'location', and 'maxSearchQueries' unexplained except by their schema names. This is insufficient for a tool with five parameters.

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 states a specific action ('Find leads'), defines the resource ('Google Maps places first... then live web search engines'), and clearly distinguishes itself from sibling tools by describing a full end-to-end pipeline. The priority order and sources make it unmistakable what this tool does.

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 conveys when to use this tool by presenting it as the comprehensive lead-finding solution, implicitly suggesting it over simpler siblings like search_web or extract_leads. However, it does not explicitly state when not to use it or what alternatives to choose for narrower tasks.

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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