Deeplead

Search persons with their emails and phones

persons_search

Search persons with their emails and phones. Covers professional contacts only: people in their role at a company, not private individuals. Returns only people with an email or phone, with full contact data, and charges 1 credit per returned person. Page with nextOffset. limit 0 returns only totalCount, free. saveToContacts also stores them in your contacts, where people you already had are refunded.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum people to return; 0 returns only a free count
`query`	No	Free text matched against company name, description and keywords
`offset`	No	Pagination offset; use nextOffset from the previous response
`domains`	No	Look companies up by domain, e.g. ["stripe.com"]
`hqState`	No	US state names or codes of the headquarters
`jobLevel`	No	Allowed job seniority levels
`jobTitle`	No	Matched as partial text, so "CEO" also finds "Assistant to the CEO"; combine with jobLevel to narrow
`semantic`	No	What the company is and sells, matched by meaning, e.g. "outsourced medical billing for clinics"
`hqCountry`	No	ISO alpha-2 country codes of the headquarters, e.g. ["US", "DE"]
`inCountry`	No	ISO alpha-2 country codes where the person is based
`personCity`	No	Cities where the person is based
`fundedAfter`	No	Year of the last funding round, at least; known for about 1 in 100 US companies
`personState`	No	States where the person is based
`foundedAfter`	No	Earliest founding year to include
`revenueRange`	No	Annual company revenue bands
`technologies`	No	Technologies used by the company
`employeeBands`	No	Headcount bands
`foundedBefore`	No	Latest founding year to include
`saveToContacts`	No	Save returned people to your Deeplead contacts
`jobTitleExclude`	No	Job title phrases to exclude
`organizationIds`	No	Limit to organizations from organizations_search
`monthlyVisitsMin`	No	Minimum monthly website visits; known for about 1 in 8 US companies, the rest are excluded
`employeeGrowthMin`	No	Minimum employee growth on LinkedIn in percent, e.g. 10; known for about 1 in 13 US companies
`decisionMakersOnly`	No	C-level, VP or director seniority, or a founder, owner, CEO, managing director or president title
`onePerOrganization`	No	Return at most one person per company
`industryNaicsDirect`	No	NAICS codes

Output Schema

TableJSON Schema

Name	Required	Description
`persons`	Yes
`nextOffset`	Yes
`totalCount`	Yes	With limit 0: all matching people, including those without an email or phone
`chargedCredits`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 2, 2026

changedInput schema / properties / organizationIds / description

Previous value: -"Limit to organizations from /organizations/search"New value: +"Limit to organizations from organizations_search"

Changed14 schema fields changedSep 26, 2026

addedInput schema / properties / foundedAfter / description
```
Added value: +"Earliest founding year to include"
```
addedInput schema / properties / foundedBefore / description
```
Added value: +"Latest founding year to include"
```
addedInput schema / properties / jobLevel / description
```
Added value: +"Allowed job seniority levels"
```
addedInput schema / properties / jobTitleExclude / description
```
Added value: +"Job title phrases to exclude"
```

addedInput schema / properties / limit / description

Added value: +"Maximum people to return; 0 returns only a free count"

changedInput schema / properties / limit / minimum
```
Previous value: -1New value: +0
```

addedInput schema / properties / offset / description

Added value: +"Pagination offset; use nextOffset from the previous response"

addedInput schema / properties / onePerOrganization

Added value: +{
+  "default": false,
+  "description": "Return at most one person per company",
+  "type": "boolean"
+}

addedInput schema / properties / personCity / description
```
Added value: +"Cities where the person is based"
```
addedInput schema / properties / personState / description
```
Added value: +"States where the person is based"
```
addedInput schema / properties / revenueRange / description
```
Added value: +"Annual company revenue bands"
```

addedInput schema / properties / saveToContacts

Added value: +{
+  "default": false,
+  "description": "Save returned people to your Deeplead contacts",
+  "type": "boolean"
+}

addedInput schema / properties / technologies / description
```
Added value: +"Technologies used by the company"
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": false,
+  "properties": {
+    "chargedCredits": {
+      "type": "number"
+    },
+    "nextOffset": {
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "persons": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "alternateEmails": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "city": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "companyEmployeeGrowthRate": {
+            "description": "Percent",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "companyLastFundingDate": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "companyLastFundingType": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "companyMonthlyVisits": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "companyName": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "companyWebsite": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "country": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "email": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "foundedYear": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "jobFunction": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "jobLevel": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "jobTitle": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "linkedin": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "naicsCodes": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "name": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "organizationId": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "personId": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "phone": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "phones": {
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "revenueRange": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "state": {
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "required": [
+          "personId",
+          "name",
+          "email",
+          "alternateEmails",
+          "phone",
+          "phones",
+          "linkedin",
+          "jobTitle",
+          "jobLevel",
+          "jobFunction",
+          "city",
+          "state",
+          "country",
+          "organizationId",
+          "companyName",
+          "companyWebsite",
+          "revenueRange",
+          "naicsCodes",
+          "foundedYear",
+          "companyMonthlyVisits",
+          "companyEmployeeGrowthRate",
+          "companyLastFundingType",
+          "companyLastFundingDate"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "totalCount": {
+      "description": "With limit 0: all matching people, including those without an email or phone",
+      "type": "number"
+    }
+  },
+  "required": [
+    "totalCount",
+    "nextOffset",
+    "chargedCredits",
+    "persons"
+  ],
+  "type": "object"
+}

First observedSep 25, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare a non-read-only, non-open-world, non-destructive profile, so the bar is lower. The description nonetheless adds substantive context beyond them: 1 credit per returned person, refunds for already-stored contacts, a free count via limit 0, and the saveToContacts side effect on the contacts store.

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

Conciseness4/5

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

Six dense sentences, front-loaded with the core verb+resource+scope before cost and pagination details. Every sentence carries information, though the limit/offset and saveToContacts notes partly duplicate the schema and could be trimmed.

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?

With an output schema present (so return values need not be explained) and 100% schema coverage, the description still covers purpose, scope, cost, pagination, and the saveToContacts side effect. It omits auth/rate-limit context, but for a search tool of this complexity it is largely complete.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 26 parameters; this is the baseline 3. The description echoes a few of them (limit 0 free count, nextOffset pagination, saveToContacts storage) without adding syntax or format detail the schema lacks.

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

Purpose4/5

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

The description states a specific verb and resource ('Search persons with their emails and phones') and adds a scope restriction ('professional contacts only ... not private individuals'). It distinguishes the domain from a likely private-individual lookup sibling, but does not name an alternative tool, so it stops short of full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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

It gives a clear usage condition and an implicit exclusion ('people in their role at a company, not private individuals'), plus cost-aware guidance ('limit 0 returns only totalCount, free'). It does not explicitly route the agent to an alternative sibling when the exclusion applies, so the guidance is clear but not complete.

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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