Skip to main content
Glama
adamanz

Apollo.io MCP Server

by adamanz

people_enrichment

Enhance contact profiles by adding professional details like company information, LinkedIn data, and email addresses using provided names or domains.

Instructions

Use the People Enrichment endpoint to enrich data for 1 person

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
first_nameNoPerson's first name
last_nameNoPerson's last name
emailNoPerson's email address
domainNoCompany domain
organization_nameNoOrganization name
linkedin_urlNoPerson's LinkedIn profile URL

Implementation Reference

  • Core handler implementing people_enrichment by POSTing to Apollo.io /people/match API endpoint with error handling.
    async peopleEnrichment(query: PeopleEnrichmentQuery): Promise<any> {
      try {
        const url = `${this.baseUrl}/people/match`;
        console.log('url', url);
        console.log('query', query);
        const response = await this.axiosInstance.post(url, query);
        
        if (response.status === 200) {
          return response.data;
        } else {
          console.error(`Error: ${response.status} - ${response.statusText}`);
          return null;
        }
      } catch (error: any) {
        console.error(`Error: ${error.response?.status} - ${error.response?.statusText || error.message}`);
        return null;
      }
    }
  • MCP CallToolRequestSchema handler dispatch case for 'people_enrichment' that calls ApolloClient.peopleEnrichment and formats response.
    case 'people_enrichment': {
      const result = await this.apollo.peopleEnrichment(args);
      return {
        content: [{
          type: 'text',
          text: JSON.stringify(result, null, 2)
        }]
      };
    }
  • src/index.ts:79-111 (registration)
    Tool registration in ListToolsRequestSchema response: defines name 'people_enrichment', description, and inputSchema.
    {
      name: 'people_enrichment',
      description: 'Use the People Enrichment endpoint to enrich data for 1 person',
      inputSchema: {
        type: 'object',
        properties: {
          first_name: { 
            type: 'string', 
            description: "Person's first name" 
          },
          last_name: { 
            type: 'string', 
            description: "Person's last name" 
          },
          email: { 
            type: 'string', 
            description: "Person's email address" 
          },
          domain: { 
            type: 'string', 
            description: "Company domain" 
          },
          organization_name: { 
            type: 'string', 
            description: "Organization name" 
          },
          linkedin_url: {
            type: 'string',
            description: "Person's LinkedIn profile URL"
          }
        }
      }
    },
  • TypeScript interface PeopleEnrichmentQuery defining the query parameters for people enrichment.
    export interface PeopleEnrichmentQuery {
      first_name?: string;
      last_name?: string;
      email?: string;
      domain?: string;
      organization_name?: string;
      [key: string]: any;
    }
  • JSON schema for tool input validation in MCP tool definition (matches PeopleEnrichmentQuery).
    inputSchema: {
      type: 'object',
      properties: {
        first_name: { 
          type: 'string', 
          description: "Person's first name" 
        },
        last_name: { 
          type: 'string', 
          description: "Person's last name" 
        },
        email: { 
          type: 'string', 
          description: "Person's email address" 
        },
        domain: { 
          type: 'string', 
          description: "Company domain" 
        },
        organization_name: { 
          type: 'string', 
          description: "Organization name" 
        },
        linkedin_url: {
          type: 'string',
          description: "Person's LinkedIn profile URL"
        }
      }
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool enriches data for one person but doesn't describe what enrichment means, what data is returned, whether it's a read-only lookup or requires authentication, rate limits, or error conditions. 'Enrich' implies adding data, but the behavioral characteristics are undefined.

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 a single, efficient sentence that directly states the tool's function. Every word earns its place: 'Use' establishes action, 'People Enrichment endpoint' identifies the tool, 'enrich data' specifies the operation, and 'for 1 person' clarifies scope. No wasted words or redundant information.

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

Completeness2/5

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

For a tool with 6 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'enrichment' produces, how parameters should be prioritized, what happens with partial information, or error handling. The context signals indicate complexity that the description doesn't address, leaving significant gaps for agent understanding.

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 fully documents all 6 parameters. The description adds no parameter-specific information beyond implying these are inputs for person enrichment. This meets the baseline of 3 when schema coverage is high, but the description doesn't explain how parameters interact (e.g., minimal required fields) or provide usage examples.

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's purpose: 'enrich data for 1 person' with the verb 'enrich' and resource 'person'. It distinguishes from siblings like 'employees_of_company' (multiple people) and 'organization_enrichment' (different resource), but doesn't explicitly differentiate from 'people_search' which might also enrich data. The purpose is specific but could be more precise about what enrichment entails.

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 prerequisites, when to choose this over 'people_search' or 'get_person_email', or what input combinations yield best results. The agent must infer usage from the tool name and parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/adamanz/apollo-io-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server