Deeplead

Search persons with their emails and phones

persons_search

Search persons with their emails and phones. 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. Send an Idempotency-Key header to make retries safe.

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.

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

A4.3/5.0

Behavior5/5

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

The description openly discloses billing behavior ('charges 1 credit per returned person'), filtering ('Returns only people with an email or phone'), pagination ('Page with nextOffset'), a free count mode, the side effect of saveToContacts including refunds for existing contacts, and idempotency guidance. These are meaningful behavioral details that go well beyond the readOnlyHint/openWorldHint/destructiveHint annotations.

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?

The description is dense but efficient: the core purpose is front-loaded, and every subsequent sentence contributes a distinct operational fact (contact filtering, cost, pagination, free count, contacts side effect, idempotency). For a tool with 26 parameters, this is appropriately sized and avoids restating schema text.

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?

Given the tool's complexity and the fact that the input schema and output schema are rich, the description covers the non-obvious aspects an agent needs: cost, free count, pagination, contact-saving side effects, and safe retries. It is slightly incomplete only in not helping an agent distinguish this from sibling search/lookup tools by naming alternatives.

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, but the description adds useful parameter-specific meaning: it clarifies that limit=0 'returns only totalCount, free' and that saveToContacts 'stores them in your contacts, where people you already had are refunded.' It doesn't re-document all params, which is appropriate since the schema already handles them.

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 opens with a specific action and object: 'Search persons with their emails and phones,' and further narrows the scope by saying it returns only people with an email or phone. Although it doesn't explicitly contrast sibling tools like persons_lookup or persons_find_email, the verb 'search' plus the contact-data qualifier makes the intended resource clear.

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?

The description gives clear operating context: use this when you need people with contact data along with full contact information, and it explains when limit=0 is appropriate ('returns only totalCount, free') plus when to send an Idempotency-Key ('to make retries safe'). It does not explicitly name alternative tools or state when not to use it, so it misses the top tier.

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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