Lead Enrichment API
Server Details
Curated EU AI/Sec/DevTools/Fintech B2B leads, Claude-scored. MCP+x402. Free 250/mo.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.8/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: quota tracking, lead searching, and lead validation. There is no functional overlap, and descriptions clearly differentiate them.
All tools follow a consistent verb_noun pattern (get_usage, search_leads, validate_lead), making the API intuitive and predictable.
Three tools is a well-scoped set for a focused lead enrichment API, covering essential operations (check usage, search, validate) without unnecessary bloat.
The surface covers core enrichment workflows (search, validate, usage). A potential minor gap is the lack of a dedicated tool to retrieve full details for a single lead by ID, but validate_lead partially addresses this.
Available Tools
3 toolsget_usageAInspect
Return current month quota status and recent usage for the calling API key.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the output but does not mention side effects, authentication requirements, rate limits, or whether it is read-only. This is insufficient for a tool that may have implications on API key usage.
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 a single sentence of 12 words, front-loaded with key information, and contains no redundant words. It is maximally concise while still conveying purpose.
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, the description should clarify the structure of returned data (e.g., fields for quota limit, usage) to be complete. It currently only vaguely mentions 'quota status' and 'recent usage', leaving ambiguity about the exact format. Adequate for a simple query but with gaps.
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 input schema has zero parameters, so the description does not need to add parameter meaning. Baseline for 0 parameters is 4, and the description appropriately handles this by not mentioning parameters.
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 the tool returns 'current month quota status and recent usage' for the calling API key, which distinguishes it from sibling tools that deal with leads. The verb 'return' and specific resource make the purpose unambiguous.
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 implies usage when checking quota or usage of the API key, and given sibling tools are unrelated to usage, context is clear. However, no explicit when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_leadsAInspect
Search enriched B2B leads by ICP criteria.
Returns scored companies with firmographics, tech stack signals, and buying signals.
Each lead returned counts against the monthly quota.
Args:
industries: Filter by industry — AI, Blockchain, Fintech, Security, Healthcare, DevTools, Other
stages: Funding stage — Pre-seed, Seed, Series A, Series B, Series C+, Public, Unknown
regions: EU, US, APAC, MENA, Other
min_icp_score: 0-100, minimum ICP fit score
min_buying_intent: 0-100, minimum buying intent score
tech_stack_contains: must match at least one signal
max_age_days: only leads enriched within N days (1-365)
limit: leads per response (1-100)
sort_by: icp_score, buying_intent, employees, or enriched_at
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| stages | No | ||
| regions | No | ||
| sort_by | No | icp_score | |
| industries | No | ||
| max_age_days | No | ||
| min_icp_score | No | ||
| min_buying_intent | No | ||
| tech_stack_contains | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a key behavioral trait: 'Each lead returned counts against the monthly quota.' This goes beyond the input schema and annotations (none provided). However, it omits other details like rate limits, authentication requirements, or side effects, but the quota disclosure is valuable.
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 structured with a clear opening sentence followed by a list of parameters. While it is slightly verbose (e.g., repeating 'must match at least one signal' for tech_stack_contains), it is mostly efficient and front-loaded with the purpose.
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 the complexity (9 parameters, no output schema), the description covers input parameters comprehensively and explains the output ('Returns scored companies with firmographics, tech stack signals, and buying signals'). The quota warning completes the context for usage.
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 input schema has 0% coverage (no descriptions), so the description fully compensates. It explains each parameter with concrete examples (e.g., industries list: AI, Blockchain, etc.) and ranges (e.g., min_icp_score: 0-100). This adds essential meaning that the schema lacks.
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 the tool's purpose: 'Search enriched B2B leads by ICP criteria.' It specifies the resource (enriched B2B leads), the action (search), and the criteria (ICP). This distinguishes it from sibling tools (get_usage and validate_lead) which focus on monitoring and validation respectively.
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 implies usage for searching leads by ICP criteria but does not explicitly state when to use this tool versus alternatives, nor does it mention when not to use it. No guidance on context or exclusions is provided, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_leadBInspect
Check the freshness and website reachability of a specific lead.
Args:
lead_id: UUID of the lead to validate
| Name | Required | Description | Default |
|---|---|---|---|
| lead_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description should disclose side effects, but only says 'check' without specifying read-only or output format; minimal behavioral context.
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?
Very concise: two sentences plus Args line. No unnecessary information.
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?
Lacks output schema or return value description; does not address error cases or validation specifics beyond basic freshness/website reachability.
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?
Description adds that lead_id is a UUID, supplementing the raw schema, but doesn't explain how the parameter affects validation.
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?
Clearly states it checks freshness and website reachability of a lead, and is distinct from siblings 'get_usage' and 'search_leads'.
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?
No guidance on when to use this tool versus alternatives; lacks any context about prerequisites or scenarios.
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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