Remote MCP server to enrich company profiles with structured B2B data and confidence scores.
Scored across 1 tool
Only one tool exists, so there is no ambiguity—agents have no risk of selecting the wrong tool.
With a single tool, naming consistency is trivial; the tool name 'enrich_lead' is clear and follows a verb_noun pattern.
One tool for a 'B2B Lead Enrichment' server is borderline - it can work if the tool encapsulates all enrichment needs, but typically such servers benefit from multiple specialized tools (e.g., batch enrichment, search, status).
The tool covers multiple enrichment dimensions (firmographic, technographic, intent, contact), but lacks batch operations, updates, or status tracking, leaving significant gaps for common workflows.
Enrich a B2B company profile with structured firmographic, technographic, intent, and contact data. This tool should be called when an AI agent needs to gather detailed information about a company before crafting a personalized outreach, generating a lead score, or making a sales recommendation.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | The company domain to enrich (e.g., "stripe.com"). | |
| attributes | No | Which data attributes to include. Allowed values: firmographic, technographic, intent, contacts. | |
| requiredFields | No | Specific fields that must be present in the response. |
| Name | Required | Description |
|---|---|---|
| revenue | Yes | Estimated annual revenue range (e.g., "$1B+"). |
| contacts | No | Key contacts identified at the company. |
| industry | Yes | Primary industry classification. |
| insights | Yes | Actionable semantic insights derived from the data. |
| enrichedAt | Yes | ISO 8601 timestamp when this enrichment was performed. |
| companyName | Yes | Official legal name of the enriched company. |
| technologies | Yes | Technology stack associated with the company. |
| employeeCount | Yes | Estimated employee count range (e.g., "5000+"). |
| intentSignals | Yes | Signals showing buying intent or strategic initiatives. |
| confidenceScore | Yes | Confidence score from 0 to 1. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds detail about the types of data collected (firmographic, technographic, intent, contacts). Although it doesn't mention error handling or auth, the read-only nature is clear.
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 that are front-loaded with purpose. No redundant information; every sentence is essential.
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 presence of an output schema (not shown) and full parameter descriptions, the tool definition is fairly complete. Missing are potential error conditions or rate limits, but overall it provides enough 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?
Schema coverage is 100%, so baseline is 3. The description does not add significant semantic value beyond the schema; the parameter descriptions are self-contained. It hints at attribute categories but doesn't detail them.
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 verb 'Enrich' and resource 'B2B company profile' with specific data types (firmographic, technographic, etc.). It distinguishes the tool's purpose well, and with no sibling tools, it's 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 explicitly states when to use the tool: before personalized outreach, lead scoring, or sales recommendations. While it provides good context, it lacks when-not-to-use guidance or alternatives, but siblings are absent.
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.
enrich_lead7 fields changedInput schema / properties / attributes / descriptionPrevious value: -"Which data attributes to include: firmographic, technographic, intent, contacts"New value: +"Which data attributes to include. Allowed values: firmographic, technographic, intent, contacts."Input schema / properties / attributes / titleAdded value: +"Attributes"Input schema / properties / domain / descriptionPrevious value: -"The company domain to enrich"New value: +"The company domain to enrich (e.g., \"stripe.com\")."Input schema / properties / domain / titleAdded value: +"Domain"Input schema / properties / requiredFields / descriptionPrevious value: -"Specific fields that must be present in the response"New value: +"Specific fields that must be present in the response."Input schema / properties / requiredFields / titleAdded value: +"Required Fields"Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "companyName": {
+ "description": "Official legal name of the enriched company.",
+ "type": "string"
+ },
+ "confidenceScore": {
+ "description": "Confidence score from 0 to 1.",
+ "maximum": 1,
+ "minimum": 0,
+ "type": "number"
+ },
+ "contacts": {
+ "description": "Key contacts identified at the company.",
+ "items": {
+ "properties": {
+ "department": {
+ "type": "string"
+ },
+ "linkedin": {
+ "type": "string"
+ },
+ "name": {
+ "type": "string"
+ },
+ "title": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "name",
+ "title",
+ "department"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "employeeCount": {
+ "description": "Estimated employee count range (e.g., \"5000+\").",
+ "type": "string"
+ },
+ "enrichedAt": {
+ "description": "ISO 8601 timestamp when this enrichment was performed.",
+ "format": "date-time",
+ "type": "string"
+ },
+ "industry": {
+ "description": "Primary industry classification.",
+ "type": "string"
+ },
+ "insights": {
+ "description": "Actionable semantic insights derived from the data.",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "intentSignals": {
+ "description": "Signals showing buying intent or strategic initiatives.",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "revenue": {
+ "description": "Estimated annual revenue range (e.g., \"$1B+\").",
+ "type": "string"
+ },
+ "technologies": {
+ "description": "Technology stack associated with the company.",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "companyName",
+ "industry",
+ "employeeCount",
+ "revenue",
+ "technologies",
+ "intentSignals",
+ "confidenceScore",
+ "enrichedAt",
+ "insights"
+ ],
+ "type": "object"
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