CrewAI Enrichment — Give Your Crew Real Company and Contact Data

import os, requests
from crewai.tools import BaseTool
from pydantic import BaseModel, Field

class FindEmailArgs(BaseModel):
 full_name: str = Field(description="Person's full name")
 company_domain: str = Field(description="Company domain, e.g. acme.com")

class FindWorkEmail(BaseTool):
 name: str = "find_work_email"
 description: str = (
 "Find a verified work email from a full name and company domain. "
 "Returns the address and its verification status, or reports a miss "
 "with the list of sources that were tried."
 )
 args_schema: type[BaseModel] = FindEmailArgs

 def _run(self, full_name: str, company_domain: str) -> str:
 r = requests.post(
 "https://api.richapi.ai/api/v1/email_finder",
 headers={"x-api-key": os.environ["RICHAPI_KEY"]},
 json={"full_name": full_name, "company_domain": company_domain},
 ).json()
 if not r.get("success"):
 tried = [a.get("status") for a in r.get("execution_log", [])]
 return f"No email found for {full_name} at {company_domain}. sources tried: {tried}. Nothing was billed."
 return f"{r['data']['email']} (status: {r['data']['status']}, cost: 5 credits)"

@agent
def researcher(self) -> Agent:
 return Agent(config=self.agents_config["researcher"],
 tools=[FindWorkEmail()], max_iter=6)

Two details in there are doing real work.

The miss branch returns the source statuses as prose. A tool that returns null teaches the agent nothing, so it retries with the same arguments and gets the same nothing. A tool that says four sources ran, three had no data, one timed out gives the agent something to reason with: retry, try the LinkedIn URL instead, or move on.

The success branch names the cost. The agent's own context now contains what it spent, which is the cheapest budget control that exists in an autonomous loop.

This is the part that surprises people coming from a plain script. A sequential chain calls email_finder once per row. A crew with an agent that decides for itself calls it once, gets a miss, decides to try find_linkedin_url_by_name first, then calls it again. That is often the right call, and it is also three lookups where you budgeted one.

Three controls, in order of how much they help:

1. max_iter on any agent holding a paid tool. Bounds the loop. Do this one.
2. Cost in the tool's return string, as above. The agent factors spend into its own decisions.
3. A narrow tool surface. An agent given find_work_email and enrich_company behaves. An agent given a generic call_richapi(endpoint, body) will explore.

Full price only on results, scoped to the waterfall endpoints: email_finder, email_verifier and phone_finder cost zero when nothing is found. The rest bill on a successful 2xx even when the payload is thin. Tiers on /pricing.

Is there an official RichAPI tool in crewai-tools? No. You write the BaseTool, or attach the MCP server.

Does enrich_company take a domain? No, a LinkedIn URL. Give the agent find_website_by_company_name or a search step if it only has a name. Full shape in company enrichment API.

Can the crew spend my whole balance? It can spend what the tool costs times the number of calls, which is why max_iter exists and why we give you 100 free credits to watch it behave first.

Can I hand the crew a list? Use kickoff_for_each, or do the bulk pass outside the crew and let the crew reason over the results. See bulk enrich without seats.

Does it work with a local model? The API does not care what is calling it. Anything that can issue an HTTP POST works.