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masridigital

Apollo.io MCP Server

by masridigital

enrich_organization

Enrich company data with detailed information including employee count, revenue, technologies, funding, and other business intelligence by providing a domain name.

Instructions

Enrich an organization's data with detailed company information, employee count, revenue, technologies used, funding, and more. Provide domain name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesCompany domain (e.g., apollo.io)

Implementation Reference

  • The handler function that executes the enrich_organization tool. It sends a POST request to Apollo's /organizations/enrich endpoint with the provided arguments (domain), processes the organization data, and returns a formatted text summary of the enriched information including name, ID, domain, industry, description, founded year, employee count, revenue, location, contact info, social links, and technologies.
    private async enrichOrganization(args: any) {
      const response = await this.axiosInstance.post("/organizations/enrich", args);
      const org = response.data.organization;
    
      if (!org) {
        return {
          content: [
            {
              type: "text",
              text: "No organization found with the provided domain.",
            },
          ],
        };
      }
    
      let result = `Organization Enrichment Results:\n\n`;
      result += `Name: ${org.name}\n`;
      result += `ID: ${org.id}\n`;
      result += `Domain: ${org.website_url || org.primary_domain || "N/A"}\n`;
      result += `Industry: ${org.industry || "N/A"}\n`;
      result += `Description: ${org.short_description || "N/A"}\n`;
      result += `Founded: ${org.founded_year || "N/A"}\n`;
      result += `Employees: ${org.estimated_num_employees || "N/A"}\n`;
      result += `Revenue: ${org.annual_revenue ? `$${org.annual_revenue}` : "N/A"}\n`;
      result += `Location: ${org.city ? `${org.city}, ${org.state || org.country}` : "N/A"}\n`;
      result += `Phone: ${org.phone || "N/A"}\n`;
      result += `LinkedIn: ${org.linkedin_url || "N/A"}\n`;
      result += `Facebook: ${org.facebook_url || "N/A"}\n`;
      result += `Twitter: ${org.twitter_url || "N/A"}\n\n`;
    
      if (org.technologies) {
        result += `Technologies Used: ${org.technologies.join(", ")}\n`;
      }
    
      return {
        content: [
          {
            type: "text",
            text: result,
          },
        ],
      };
    }
  • The input schema definition for the enrich_organization tool, specifying that it requires a 'domain' string parameter.
    {
      name: "enrich_organization",
      description:
        "Enrich an organization's data with detailed company information, employee count, revenue, technologies used, funding, and more. Provide domain name.",
      inputSchema: {
        type: "object",
        properties: {
          domain: {
            type: "string",
            description: "Company domain (e.g., apollo.io)",
          },
        },
        required: ["domain"],
      },
    },
  • src/index.ts:68-69 (registration)
    Registration in the tool dispatch switch statement within the CallToolRequestSchema handler, mapping the tool name to the enrichOrganization method.
    case "enrich_organization":
      return await this.enrichOrganization(args);
  • src/index.ts:257-257 (registration)
    Tool name registration in the getTools() method's tools array, used for ListToolsRequestSchema.
    name: "enrich_organization",
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 implies a read-only enrichment operation but doesn't disclose behavioral traits: whether it's idempotent, requires authentication, has rate limits, returns structured or unstructured data, or handles errors. For a tool with no annotation coverage, this is a significant gap in transparency.

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 concise (two sentences) and front-loaded with the core purpose. The first sentence efficiently lists enrichment targets, and the second clarifies the required parameter. No wasted words, though it could be slightly more structured (e.g., separating usage notes).

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?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'enrich' entails operationally (e.g., fetches external data, updates internal records), the return format, or error handling. For a tool that likely queries external APIs or databases, more context is needed to guide the agent effectively.

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%, with one parameter ('domain') fully documented in the schema. The description adds minimal value beyond the schema by specifying 'Provide domain name' and giving an example ('apollo.io'), but doesn't explain format constraints (e.g., must be a valid domain) or edge cases. Baseline 3 is appropriate as the schema does the heavy lifting.

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 an organization's data with detailed company information' and lists specific data types (employee count, revenue, technologies, funding). It distinguishes from siblings like 'search_organizations' (which likely finds organizations) and 'enrich_person' (which targets individuals). However, it doesn't explicitly contrast with 'get_account' or 'create_account', leaving some ambiguity.

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 (e.g., needing a domain), exclusions (e.g., not for personal data), or compare to siblings like 'search_organizations' (which might retrieve basic info) or 'get_account' (which might fetch existing account data). The agent must infer usage from the name and description alone.

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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