Fullenrich MCP connector for AI agents

Tools your prospecting agent reaches for on Fullenrich, scoped per user.

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13 tools for B2B contact data: search people and companies, launch email and phone enrichment jobs, look up contacts by email, check credits, and export results.

fullenrichmcp_enrich_bulk

Enrich bulk

Launch an asynchronous bulk enrichment job for a list of contacts, retrieving professional email addresses or phone numbers. Returns an enrichment ID and URL to track results.

Parameters

Name

Type

Required

Description

contacts

string

Required

List of contacts to enrich

fields

string

Required

Enrichment fields to request

name

string

Required

Short human-readable label for this enrichment (e.g. Google Engineers Emails)

fullenrichmcp_enrich_search_contact

Enrich search contact

Launch an asynchronous enrichment job for contacts matching search filters, enriching them with professional emails or phone numbers. Returns an enrichment ID to track progress.

Parameters

Name

Type

Required

Description

fields

string

Required

required,Enrichment fields to request

current_company_days_since_last_job_change

string

Optional

Filter by days since last job change

current_company_domains

string

Optional

Filter by current company domain

current_company_founded_years

string

Optional

Filter by current company founded year range

current_company_headcounts

string

Optional

Filter by current company employee count range

current_company_headquarters

string

Optional

Filter by current company HQ location

current_company_ids

string

Optional

Filter by current company ID

current_company_industries

string

Optional

Filter by current company industry

current_company_linkedin_urls

string

Optional

Filter by current company LinkedIn URL

current_company_names

string

Optional

Filter by current company name

current_company_revenue_ranges

string

Optional

Filter by current company annual revenue range

current_company_specialties

string

Optional

Filter by current company specialties

current_company_types

string

Optional

Filter by current company type

current_company_years_at

string

Optional

Filter by years at current company

current_position_seniority_level

string

Optional

Filter by seniority level (Director, VP, or C-level)

current_position_titles

string

Optional

Filter by current job title

current_position_years_in

string

Optional

Filter by years in current position

limit

integer

Optional

Number of contacts to enrich (default: 100, max: 10000)

offset

integer

Optional

Number of results to skip

past_company_domains

string

Optional

Filter by past company domains

past_company_names

string

Optional

Filter by past company names

past_position_titles

string

Optional

Filter by past job titles

person_ids

string

Optional

Filter by person ID

person_linkedin_urls

string

Optional

Filter by LinkedIn profile URL

person_locations

string

Optional

Filter by location (city, region, or country)

person_names

string

Optional

Filter by name (first, last, or full)

person_skills

string

Optional

Filter by skills

person_universities

string

Optional

Filter by university attended

fullenrichmcp_export_companies

Export companies

fullenrichmcp_export_contacts

Export contacts

Export contact search results to a CSV or JSON file. Use this when you need more than 10 results. Returns a download URL valid for 24 hours.

Parameters

Name

Type

Required

Description

format

string

Required

required. One of: `csv`, `json`.

current_company_days_since_last_job_change

string

Optional

Filter by days since last job change

current_company_domains

string

Optional

Filter by current company domain

current_company_founded_years

string

Optional

Filter by current company founded year range

current_company_headcounts

string

Optional

Filter by current company employee count range

current_company_headquarters

string

Optional

Filter by current company HQ location

current_company_ids

string

Optional

Filter by current company ID

current_company_industries

string

Optional

Filter by current company industry

current_company_linkedin_urls

string

Optional

Filter by current company LinkedIn URL

current_company_names

string

Optional

Filter by current company name

current_company_revenue_ranges

string

Optional

Filter by current company annual revenue range

current_company_specialties

string

Optional

Filter by current company specialties

current_company_types

string

Optional

Filter by current company type

current_company_years_at

string

Optional

Filter by years at current company

current_position_seniority_level

string

Optional

Filter by seniority level (Director, VP, or C-level)

current_position_titles

string

Optional

Filter by current job title

current_position_years_in

string

Optional

Filter by years in current position

limit

integer

Optional

Maximum number of results to export (default: 100, max: 10000)

offset

integer

Optional

Number of results to skip before exporting

past_company_domains

string

Optional

Filter by past company domains

past_company_names

string

Optional

Filter by past company names

past_position_titles

string

Optional

Filter by past job titles

person_ids

string

Optional

Filter by person ID

person_linkedin_urls

string

Optional

Filter by LinkedIn profile URL

person_locations

string

Optional

Filter by location (city, region, or country)

person_names

string

Optional

Filter by name (first, last, or full)

person_skills

string

Optional

Filter by skills

person_universities

string

Optional

Filter by university attended

fullenrichmcp_export_enrichment_results

Export enrichment results

fullenrichmcp_get_credits

Get credits

fullenrichmcp_get_enrichment_results

Get enrichment results

fullenrichmcp_list_functions_subfunctions

List functions subfunctions

fullenrichmcp_list_industries

List industries

fullenrichmcp_list_seniorities

List seniorities

fullenrichmcp_search_companies

Search companies

fullenrichmcp_search_contact_by_email

Search contact by email

fullenrichmcp_search_people

Search people

Search for contacts in the FullEnrich database using filters such as name, company, job title, location, and skills. Returns up to 10 preview results.

Parameters

Name

Type

Required

Description

current_company_days_since_last_job_change

string

Optional

Filter by days since last job change

current_company_domains

string

Optional

Filter by current company domain

current_company_founded_years

string

Optional

Filter by current company founded year range

current_company_headcounts

string

Optional

Filter by current company employee count range

current_company_headquarters

string

Optional

Filter by current company HQ location

current_company_ids

string

Optional

Filter by current company ID

current_company_industries

string

Optional

Filter by current company industry

current_company_keywords

string

Optional

Filter by current company keywords

current_company_linkedin_urls

string

Optional

Filter by current company LinkedIn URL

current_company_names

string

Optional

Filter by current company name

current_company_revenue_ranges

string

Optional

Filter by current company annual revenue range

current_company_specialties

string

Optional

Filter by current company specialties

current_company_technologies

string

Optional

Filter by technologies used by the current company (e.g. Salesforce, HubSpot, AWS)

current_company_types

string

Optional

Filter by current company type

current_company_years_at

string

Optional

Filter by years at current company

current_position_function_sub_functions

string

Optional

Filter by job function (and optional subfunction). Each entry pairs a Function with an optional SubFunction belonging to it.

current_position_seniority_level

string

Optional

Filter by seniority level

current_position_titles

string

Optional

Filter by current job title

current_position_years_in

string

Optional

Filter by years in current position

include_descriptions

boolean

Optional

If true, include description fields (company descriptions, position descriptions) in the response. Default false to save tokens.

limit

integer

Optional

Number of results to return (max 10)

max_per_company

integer

Optional

Limit results to at most N contacts per company

past_company_domains

string

Optional

Filter by past company domains

past_company_linkedin_urls

string

Optional

Filter by past company LinkedIn URL

past_company_names

string

Optional

Filter by past company names

past_position_titles

string

Optional

Filter by past job titles

person_ids

string

Optional

Filter by person ID

person_languages

string

Optional

Filter by languages

person_linkedin_urls

string

Optional

Filter by LinkedIn profile URL

person_locations

string

Optional

Filter by location (city, region, or country)

person_names

string

Optional

Filter by name (first, last, or full)

person_skills

string

Optional

Filter by skills

person_universities

string

Optional

Filter by university attended

Build your Agent

Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.

import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Fullenrich MCP tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fullenrichmcp"], toolNames: [
    "fullenrichmcp_search_people",
    "fullenrichmcp_enrich_bulk",
    "fullenrichmcp_get_enrichment_results"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Find VP Sales contacts at fintech companies in New York" }] });

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fullenrichmcp"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Find VP Sales contacts at fintech companies in New York" }],
  tools,
});

// Execute the tool call with the user's vaulted Fullenrich token
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fullenrichmcp"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Find VP Sales contacts at fintech companies in New York" }],
  tools,
});

// Tool call runs with the user's vaulted Fullenrich token
await sk.tools.executeTool(msg.content, "user_123");

import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["fullenrichmcp"] }, pageSize: 100,
});

const agent = new Agent({
  name: "prospecting_agent",
  model: "gemini-2.5-pro",
  instruction: "Fullenrich MCP tools scoped to this user",
  tools,
});

await agent.run("Find VP Sales contacts at fintech companies in New York");

Try these prompts

Copy any prompt into your agent. Each maps directly to a Fullenrich MCP tool. Click to copy, paste into your agent, done.

Copy the prompt

Copied

Find VP Sales contacts at fintech companies in New York.

Copy the prompt

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Search for software companies with 50 to 200 employees in Germany.

Copy the prompt

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List the seniority levels I can filter people search on.

Enrich

Copy the prompt

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Enrich these 50 contacts with professional emails.

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Find phone numbers for the people matching this search.

Copy the prompt

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Look up the contact profiles behind these email addresses.

Jobs and credits

Copy the prompt

Copied

Check the status of my latest enrichment job.

Copy the prompt

Copied

Export all results from this enrichment job to CSV.

Copy the prompt

Copied

How many credits are left in my workspace?

SEE HOW AUTH WORKS

Each user signs in to Fullenrich once; Scalekit stores and refreshes their tokens. Credentials stay vaulted, every call is scope checked, and every action is logged.

Authorize

Your user connects

Fullenrich MCP

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Fullenrich MCP

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Fullenrich MCP

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Fullenrich MCP

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other sales and prospecting connectors.

GTM and RevOps Teams

Outbound prospecting agent

Searches Apollo for prospects matching your ICP, scores and ranks them, drafts personalized outreach in Gmail, and logs every send to Google Sheets. Mail goes out as the rep, not from a shared inbox.

GTM and RevOps Teams

CRM AI agent

Reads the Granola transcript after every call, extracts next steps and updates the HubSpot record, drafts the follow-up in Gmail, and confirms in Slack, all on the rep's own delegated OAuth.

GTM and RevOps Teams

Deal intelligence agent

Pulls recent Gong calls, scores deal risk with an LLM, cross-references the record in Attio, and DMs each owner their at-risk deals in Slack. Every read is scoped to that rep's own access.

GTM and RevOps Teams

Sales call prep agent

Reads tomorrow's calls from Google Calendar, mines past Granola notes and Attio history for context, and delivers each rep a prep brief in Slack, scoped to the calls that rep actually owns.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared Fullenrich token looks fine in a demo. In production every search and enrichment job looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.

// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Fullenrich today. Ten connectors tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Fullenrich as the user or through a shared service account?

As the user. Each user signs in to Fullenrich once, and Scalekit stores and refreshes their tokens. Audit logs attribute every action to that user, not a shared service account.

Where is the Fullenrich OAuth token stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.

Can I limit what the agent does in Fullenrich?

Yes. Filter by tool name in listScopedTools to expose only what you want, for example the 10 read-only search and export tools without the enrichment jobs. Scalekit also enforces scope checks before every API call.

What happens when a user revokes Fullenrich access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

How does the agent get enrichment results?

Enrichment runs as an asynchronous job. fullenrichmcp_enrich_bulk, fullenrichmcp_enrich_search_contact, and fullenrichmcp_search_contact_by_email each return an enrichment ID. The agent checks status and up to 10 rows with fullenrichmcp_get_enrichment_results, then pulls the full dataset as CSV or JSON with fullenrichmcp_export_enrichment_results.