Generect

Enrich one lead

enrich_lead

Full profile for one known person, by Generect id, LinkedIn URL or work email (reverse lookup). Billable: about $0.02 per record found (not-found is refunded) at the Tier 0 list price. Accounts can pay a different rate: get_balance returns this account's prices, and every response reports what was actually spent in cost.amount_charged_usd. Not found costs nothing. The id from a search or preview result is the most accurate identifier. start_bulk_job handles many people at once.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "enrich_lead"
  }
}

Input Schema

Name	Required	Description
`id`	No	Generect lead id from search/preview.
`mode`	No	Data mode. "database" = Generect's own index: sub-second, free counts, free thin rows (see detail) or cheaper full rows; it accepts a subset of the filters today and names any it rejects. "realtime" = live LinkedIn lookup, 5–60s, billed per row, accepts every realtime filter. "auto" (default) tries database first and escalates to realtime only if a filter you passed is rejected there (the escalation is reported, and is refused above the per-call spend ceiling). Pick "database" explicitly when a record from the last 12 months is good enough and cost matters more than freshness.
`email`	No	Work email, for reverse lookup.
`compact`	No	Default true: return a small per-lead summary (including the Generect `id`, which every later step accepts). Set false for the full raw record (~80 fields), only worth it when you specifically need skills, education or other deep fields.
`timeout_ms`	No	Request timeout in milliseconds.
`linkedin_url`	No	LinkedIn profile URL.

Output Schema

Name	Required	Description	Default
`cost`	No
`lead`	No
`mode`	No
`found`	No
`company`	No
`test_mode`	No
`test_mode_notice`	No
`vocabulary_warnings`	No
`deprecated_params_ignored`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 9, 2026

changedInput schema / properties / compact / description

Previous value: -"Default true: return a small per-lead summary (including the Generect `id`, which every later step accepts). Set false for the full raw record (~80 fields) — only worth it when you specifically need skills, education or other deep fields."New value: +"Default true: return a small per-lead summary (including the Generect `id`, which every later step accepts). Set false for the full raw record (~80 fields), only worth it when you specifically need skills, education or other deep fields."

Changed5 schema fields changedOct 7, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

removedInput schema / additionalProperties
```
Removed value: -false
```

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

addedOutput schema / properties / deprecated_params_ignored / propertyNames
```
Added value: +{
+  "type": "string"
+}
```
addedOutput schema / properties / vocabulary_warnings / items
```
Added value: +{}
```

Changed1 schema field changedOct 6, 2026

changedInput schema / properties / mode / description

Previous value: -"Data mode. \"database\" = cached, sub-second, cheaper, free counts, core filters only. \"realtime\" = live LinkedIn lookup, 5–60s, pricier, supports every filter. \"auto\" (default) tries database first and only escalates to realtime if a filter you passed is unsupported there — an escalation is reported in the response. Pick \"database\" explicitly when a record from the last 12 months is good enough and cost matters more than freshness."New value: +"Data mode. \"database\" = Generect's own index: sub-second, free counts, free thin rows (see detail) or cheaper full rows; it accepts a subset of the filters today and names any it rejects. \"realtime\" = live LinkedIn lookup, 5–60s, billed per row, accepts every realtime filter. \"auto\" (default) tries database first and escalates to realtime only if a filter you passed is rejected there (the escalation is reported, and is refused above the per-call spend ceiling). Pick \"database\" explicitly when a record from the last 12 months is good enough and cost matters more than freshness."

Changed1 schema field changedSep 24, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "company": {},
+    "cost": {
+      "additionalProperties": false,
+      "properties": {
+        "amount_charged_usd": {
+          "type": [
+            "number",
+            "null"
+          ]
+        },
+        "billed": {
+          "type": "string"
+        },
+        "note": {
+          "type": "string"
+        },
+        "operation": {
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "deprecated_params_ignored": {
+      "additionalProperties": {
+        "type": "string"
+      },
+      "type": "object"
+    },
+    "found": {
+      "type": "boolean"
+    },
+    "lead": {},
+    "mode": {
+      "type": "string"
+    },
+    "test_mode": {
+      "type": "boolean"
+    },
+    "test_mode_notice": {
+      "type": "string"
+    },
+    "vocabulary_warnings": {
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

AddedSep 10, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only declare the openWorld/non-read-only posture; the description adds the material economics the agent cannot infer: ~$0.02 per record at Tier 0 list, per-account rates via get_balance, not-found is refunded, and the actual charge is reported in cost.amount_charged_usd. That is exactly the kind of non-obvious consequence (billable side effect with refund rule) the annotations do not carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Five sentences, no filler: identity/scope first, then cost, then identifier preference, then the bulk alternative. The pricing sentences are dense but every clause (refund rule, per-account rate, where the charge appears) changes how the agent should call it.

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?

An output schema exists and the description correctly declines to re-explain return shapes, while still calling out cost.amount_charged_usd. The one real hole is the zero-required-parameters contract: it implies 'id, LinkedIn URL or work email' but never states that at least one is needed or what happens if two are passed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3; the description earns one step by adding ranking guidance the schema does not give — that the Generect `id` is the most accurate identifier and that email is a reverse lookup. It stops short of stating precedence when several identifiers are supplied at once, which matters because the schema marks zero required parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Full profile for one known person') and enumerates the three accepted identifier types, including the reverse-lookup case for email. An agent can distinguish this from enrich_company, search_leads and preview_leads 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.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit routing: 'The `id` from a search or preview result is the most accurate identifier' selects between identifier types, and 'start_bulk_job handles many people at once' names the alternative for batch work. It also points at get_balance for account-specific pricing, so the when-to-use question is answered rather than implied.

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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