# Person Enrichment MCP (`theona/person-enrichment-mcp`) Actor

MCP server that turns an email, a LinkedIn URL or a sentence about someone into one verified profile of the person and their company, with conflicts between sources spelled out instead of guessed.

- **URL**: https://apify.com/theona/person-enrichment-mcp.md
- **Developed by:** [Theona](https://apify.com/theona) (community)
- **Categories:** MCP servers
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Person Enrichment MCP

An MCP server that identifies a person from partial information and returns one structured profile.

Give the tool whatever you know about someone — a name, an email, a LinkedIn URL, or a sentence like "the CTO of Acme who spoke at re:Invent" — and it returns what could actually be verified. Every field carries a confidence score from 0 to 1 and names its source. Anything it could not establish is left out rather than guessed. When two sources disagree, it keeps the one it trusts, lowers the confidence and records the disagreement. When more than one real person fits, it returns the candidates instead of choosing.

It reads only: it connects to nothing of yours and writes nothing anywhere. It returns no home addresses, personal phone numbers or family details, even where a source offers them — only what a person has published about themselves professionally, or what a business data provider publishes about them in that capacity.

### Tool

`person_enrichment` — takes `query` (the text or identifier you have) and returns one JSON object:

| Field | Meaning |
| --- | --- |
| `status` | `found`, `ambiguous`, `no_match` or `insufficient_input` |
| `person` | The profile, each field with its confidence and source |
| `company` | The person's current company |
| `signals` | Notable recent activity |
| `conflicts` | Where sources disagreed, and which value was kept |
| `candidates` | Every plausible match, when the input fits more than one person |
| `notes` | What was attempted |
| `queried_at` | When the lookup ran |

### Credentials

Two are needed:

- **Your Apify API token**, in the `Authorization` header, as for any Apify MCP server.
- **Your Theona access key**, in the `X-Theona-Api-Key` header. The lookup runs on your own Theona account. Get the key at [app.theona.ai/mcp](https://app.theona.ai/mcp?endpoint=person-enrichment\&label=Apify); it opens this one agent and can be revoked on the same page.

#### Claude Code

```bash
claude mcp add --transport http person-enrichment \
  https://theona--person-enrichment-mcp.apify.actor/mcp \
  --header "Authorization: Bearer <APIFY_TOKEN>" \
  --header "X-Theona-Api-Key: <THEONA_ACCESS_KEY>"
```

#### Clients that accept custom headers

```json
{
  "mcpServers": {
    "person-enrichment": {
      "url": "https://theona--person-enrichment-mcp.apify.actor/mcp",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>",
        "X-Theona-Api-Key": "<THEONA_ACCESS_KEY>"
      }
    }
  }
}
```

### Costs

Apify bills the platform usage of the Standby run. Lookups count against your Theona plan.

### Support

Open an issue on this Actor's Issues tab.

# Actor input Schema

## Actor input object example

```json
{}
```

# Actor output Schema

## `endpointCheck` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("theona/person-enrichment-mcp").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("theona/person-enrichment-mcp").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call theona/person-enrichment-mcp --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,theona/person-enrichment-mcp"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/UvcbauIL6xmYI8d8c/builds/qKDpbwnBU3xG9rBjs/openapi.json