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OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

discover_prospects

Read-only

Find real companies likely to buy your product by searching the web for current buying signals like hiring, launches, or funding, with linked evidence.

Instructions

Finds real companies likely to buy your product. Searches the web for companies showing they have the problem you solve right now (hiring, launches, funding, expansion) and links the page behind every piece of evidence. Uses the product saved on your account. Takes up to a couple of minutes; nothing is charged if no company has sourced evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
industryNoTarget industry to search within
companyNameNoYour company name. Defaults to the product saved on your account.
targetMarketNoTarget market segment (e.g., "Series A SaaS companies")
coreCapabilityNoThe single most important thing your product does — the core capability that makes customers buy
productDescriptionNoWhat your product does and who it's for. Defaults to the product saved on your account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.4.4
    • changedInput schema / properties / companyName / description
      Previous value: -"Your company name"New value: +"Your company name. Defaults to the product saved on your account."
    • changedInput schema / properties / productDescription / description
      Previous value: -"What your product does and who it's for. Infer from conversation context if the user has already described their product."New value: +"What your product does and who it's for. Defaults to the product saved on your account."
    • removedInput schema / required
      Removed value: -[
-  "companyName",
-  "productDescription"
-]
  2. First observedv1.4.0

TDQS

A3.9/5.0
Behavior5/5

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

Annotations only cover readOnlyHint and openWorldHint. The description adds genuinely new behavioral facts: it can take up to a couple of minutes (latency), nothing is charged when no company has sourced evidence (a conditional billing model), and every piece of evidence is backed by a linked source page (output trust model). That is exactly the extra context annotations cannot carry.

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?

Three tight sentences, front-loaded with the core purpose before the mechanism and the operational caveats. No filler, though the latency/billing sentence could be slightly more compact. Every sentence adds information.

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

Completeness4/5

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

With no output schema, the description carries the return-value burden, and it handles that by stating that every claim is backed by a linked evidence page. It also covers latency and cost. All five parameters are optional and schema-covered, so the remaining gap is minor (no guidance on result volume or how to narrow a search).

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?

Schema coverage is 100%, so each of the five parameters is already documented in the input schema, including the 'defaults to the product saved on your account' behavior for companyName and productDescription. The description's mention of the saved product context repeats rather than extends the schema, so the baseline 3 applies.

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?

States a concrete verb and resource: 'Finds real companies likely to buy your product', amplified by 'Searches the web for companies showing they have the problem you solve right now'. An agent can immediately tell this is a web-sourced prospect discovery tool, distinct from the get_*/list_* siblings. It stops short of explicitly naming any sibling, so it doesn't earn a 5.

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?

Usage is implied rather than prescribed: it explains the signal types it looks for (hiring, launches, funding, expansion) and that it runs against the saved product context, which tells an agent when this is the relevant tool. But there is no explicit when-to-use vs. an alternative, and no stated prerequisites (e.g. needing product context set first) beyond the soft 'uses the product saved on your account'.

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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