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Apollo.io MCP Server

search_people

Find business contacts in Apollo.io by job title, company, location, or seniority to access employment details and contact information for sales and marketing purposes.

Instructions

Search for people/contacts in Apollo.io database.

This tool allows you to search for people by job title, seniority, company domain, location, and other criteria. Returns contact information and employment details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the 'search_people' tool. Decorated with @mcp.tool() for FastMCP registration. Parses and validates input using PeopleSearchRequest schema, calls Apollo.io API /v1/mixed_people/search endpoint, handles JSON input and errors.
    @mcp.tool()
    async def search_people(request: Union[Dict[str, Any], str]) -> Dict[str, Any]:
        """
        Search for people/contacts in Apollo.io database.
        
        This tool allows you to search for people by job title, seniority, company domain,
        location, and other criteria. Returns contact information and employment details.
        """
        endpoint = "/v1/mixed_people/search"
        
        # Handle both JSON string and dict inputs
        if isinstance(request, str):
            try:
                request = json.loads(request)
            except json.JSONDecodeError as e:
                return {"error": f"Invalid JSON in request: {str(e)}"}
        
        # Create and validate request object from dictionary
        try:
            people_request = PeopleSearchRequest(**request)
        except Exception as e:
            return {"error": f"Invalid request parameters: {str(e)}"}
        
        # Convert request to dict and remove None values
        search_params = {k: v for k, v in people_request.dict().items() if v is not None}
        
        try:
            result = await apollo_client.make_request("POST", endpoint, data=search_params)
            return result
        except httpx.HTTPStatusError as e:
            return {"error": f"API request failed: {e.response.status_code} {e.response.text}"}
        except Exception as e:
            return {"error": f"Request failed: {str(e)}"}
  • Pydantic BaseModel schema used for input validation in the search_people handler. Defines optional search parameters like organization domains, titles, seniorities, locations, employee ranges, pagination.
    class PeopleSearchRequest(BaseModel):
        """Request model for people search."""
        q_organization_domains: Optional[str] = Field(None, description="Organization domains (newline separated)")
        person_titles: Optional[List[str]] = Field(None, description="Job titles to search for")
        person_seniorities: Optional[List[str]] = Field(None, description="Seniority levels")
        organization_locations: Optional[List[str]] = Field(None, description="Organization locations")
        organization_num_employees_ranges: Optional[List[str]] = Field(None, description="Employee count ranges")
        page: int = Field(1, description="Page number for pagination")
        per_page: int = Field(10, description="Number of results per page")
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the tool returns contact information and employment details, which is helpful, but lacks critical behavioral traits: it doesn't specify if this is a read-only operation, what permissions are needed, whether there are rate limits, or how results are paginated/limited. For a search tool with no annotations, this leaves significant gaps.

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?

The description is appropriately sized with two sentences: the first states the purpose, and the second adds search criteria and return details. It's front-loaded with the core function. There's minimal waste, though it could be slightly more structured (e.g., bullet points for criteria).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (search with multiple criteria), no annotations, and an output schema that likely handles return values, the description is partially complete. It covers purpose and criteria but lacks behavioral context and detailed parameter guidance. The output schema reduces the need to explain returns, but gaps in usage and transparency remain.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It lists search criteria like job title, seniority, company domain, and location, which adds meaning beyond the generic 'request' parameter in the schema. However, it doesn't explain the parameter's structure, format, or how to combine criteria, leaving the single required parameter poorly defined.

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 clearly states the tool searches for people/contacts in the Apollo.io database, specifying the resource (people/contacts) and verb (search). It distinguishes from siblings like search_accounts and search_opportunities by focusing on people rather than accounts or opportunities. However, it doesn't explicitly contrast with enrich_person, which might retrieve details for a specific person.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose search_people over enrich_person for individual details, or how it differs from search_accounts for company-related searches. No exclusions or prerequisites are stated, leaving usage context unclear.

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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