Find B2B leads for target companies: LinkedIn profiles, job titles, and guessed business emails. Apollo and ZoomInfo alternative. No API key required.
| Name | Required | Description | Default |
|---|---|---|---|
| companies | Yes | Company names or domains (e.g. ["stripe.com", "notion.so"]) | |
| jobTitles | No | Job title filters (e.g. ["CEO", "Head of Marketing"]) | |
| maxLeadsPerCompany | No | Max leads per company (default 10) |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'guessed business emails,' indicating potential inaccuracy, but lacks information about rate limits, data freshness, source reliability, or output volume. The description does not disclose destructive or read-only nature, which is critical for a tool that scrapes or guesses data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, highly efficient, and front-loaded with the core purpose. Every word adds value—nothing is superfluous. It achieves maximum clarity with minimal length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should provide more context about return values, error handling, or limitations. It only hints at output types (profiles, titles, emails) but does not specify structure, pagination, or success criteria. For a tool with three parameters and no output schema, this is insufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds general context (e.g., 'target companies,' 'job titles') but does not provide additional meaning or format details beyond the schema. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool finds B2B leads with LinkedIn profiles, job titles, and guessed business emails. It positions itself as an alternative to Apollo and ZoomInfo and notes 'No API key required.' While it does not explicitly compare to sibling tools like find_linkedin_candidates, the unique offering of guessed emails and free access provides some differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance. It implies the tool is for lead generation and is free, but it does not specify when to use this versus sibling tools such as search_linkedin_employees or find_linkedin_candidates. There is no mention of when not to use it or prerequisites.
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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