Company enrichment API: firmographics from a domain or IP address. Identifies website visitors.
Scored across 3 tools
Each tool targets a distinct operation: account credit status, domain-based firmographic lookup, and IP-based organization identification. lookup_domain and lookup_ip share a domain but have clearly different inputs and outputs, and their descriptions explicitly cross-reference each other to guide chaining.
All three names follow a consistent snake_case verb_noun pattern (get_credit_balance, lookup_domain, lookup_ip). The only variance is get vs lookup, which reads naturally and does not break the convention.
Three tools is lean but well-matched to a narrow enrichment/lookup service with no redundant entries. It sits near the lower bound for a server covering both IP and domain enrichment, but every tool earns its place.
The core workflow (IP → domain → firmographics, plus credit visibility) is fully covered with no dead ends. Gaps exist for reverse lookup by company name or bulk/batch enrichment, but agents can work around these with the given tools.
Show how many LeadBoxer credits this account has left, with the active credit grants and their expiry dates. Does not use credits.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds genuinely non-obvious behavior: it explicitly reassures that the call consumes no credits, and it discloses the response contents (active grants and their expiry dates) in the absence of an output schema.
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?
Two short sentences, both front-loaded with the essential information (what is shown, then the no-credit-consumption caveat). No filler, no repetition of the tool name.
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?
For a zero-parameter read tool with no output schema, the description covers the key facts an agent needs: what is returned and that it is free of side effects. It stops short of describing units or the expiry-date format, which is a minor gap given the simplicity of the operation.
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?
The tool takes zero parameters and the schema is an empty object, so there is nothing to disambiguate. Baseline for a parameterless tool applies, and the description correctly implies the account scope is implicit rather than something the caller must pass.
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?
States a specific verb and resource (show remaining LeadBoxer credits for this account) and even enumerates what is reported: credit count, active grants, and their expiry dates. The sibling tools (lookup_domain, lookup_ip) are in an unrelated domain, so there is no realistic risk of an agent confusing this tool with them.
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?
Usage is only implied by the nature of the operation; there is no explicit statement of when to call this versus another tool, nor any prerequisite or alternative named. The closing line 'Does not use credits' is a useful caveat but is about side effects, not about when to select the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get firmographic details for a company by its domain name (e.g. leadboxer.com, without protocol or www). Returns company name, industry, employee count range, description, address, phone, LinkedIn URL, specialties and domain aliases. Useful to enrich CRM records, score ICP fit, or get full company details after lookup_ip returned a domain. Uses LeadBoxer credits per call.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Company domain to enrich, e.g. 'leadboxer.com' (no https://, no www). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds non-annotation context that matters operationally: 'Uses LeadBoxer credits per call,' which warns the agent of a cost per invocation.
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?
Two sentences, front-loaded with the action, followed by the return payload and the credit cost. No filler or restatement of the title.
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?
With no output schema, enumerating the returned fields (name, industry, employee range, address, aliases) is genuinely additive, and the credit cost plus the sibling handoff cover everything needed to invoke it correctly.
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 description coverage is 100% and the single parameter is fully documented there, including the same 'no https://, no www' guidance repeated in the description. Baseline 3 applies since 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?
States a specific verb and resource ('Get firmographic details for a company by its domain name') and distinguishes itself from lookup_ip by framing the domain as the input key rather than the output.
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?
Gives concrete use cases (enrich CRM records, score ICP fit) and explicitly chains from the sibling: 'get full company details after lookup_ip returned a domain.' It never states when not to use it, but the sibling routing is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Identify the organization behind an IPv4 or IPv6 address. Returns the company or organization name, its domain, ISP, usage type (business, residential, mobile, datacenter, education, government) and geolocation (country, region, city, timezone). Useful for IPs from server logs, analytics, sign-ups or security events. For full firmographics, call lookup_domain with the returned ipDomain. Uses LeadBoxer credits per call.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | The IP address to look up, IPv4 (e.g. 8.8.8.8) or IPv6. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new behavior: the exact fields returned and a cost disclosure ('Uses LeadBoxer credits per call'), which matters for budgeting. Auth requirements and rate limits remain unstated, keeping it short of a 5.
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?
Front-loaded with the core purpose, then return fields, then usage context, then sibling routing and cost. Four sentences all carry information, though the long parenthetical enumerations of usage types and geo fields are slightly dense.
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?
With no output schema, the description compensates by enumerating return fields (org name, domain, ISP, usage type, geolocation) and discloses credit consumption and the follow-up call to lookup_domain. Nearly complete for a single-parameter lookup; only error/failure behavior is unaddressed.
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?
Only one parameter with 100% schema description coverage; the schema already documents the IPv4/IPv6 example and length bounds. The description restates the IPv4/IPv6 scope but adds no format or edge-case detail beyond the schema, so baseline 3 applies.
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?
States a specific verb and resource ('Identify the organization behind an IPv4 or IPv6 address') and immediately scopes it against the sibling by noting that full firmographics require lookup_domain. An agent can distinguish this from lookup_domain and get_credit_balance without opening any schema.
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?
Gives concrete usage contexts ('server logs, analytics, sign-ups or security events') and an explicit alternative with the condition that selects it ('For full firmographics, call lookup_domain with the returned ipDomain'). No explicit when-not guidance, but the routing decision is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_credit_balancelookup_domainlookup_ipEnrich any domain into a full company profile with firmographics and buying signals.
Company enrichment for AI agents: firmographics, tech stack, headcount, funding, domain emails.
Domain & brand intelligence: company enrichment, tech stack detection, brand research.
Free — no API key required. Enrich by domain or name. Country, contacts, social profiles.
Add one secure layer between your agents and this server.
