# Maddyness French Startup fundraising database (`advantageous_subcontra/maddyness-french-startup-fundraising-database`) Actor

Retrieve information about recent French startup fundraising based on Maddyness weekly reports.

- **URL**: https://apify.com/advantageous\_subcontra/maddyness-french-startup-fundraising-database.md
- **Developed by:** [Fabian Maume](https://apify.com/advantageous_subcontra) (community)
- **Categories:** News, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.10 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## 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

**Maddyness French Startup fundraising database** return a list of **French startups** who recently raised funds. Data are based on weekly fundraising reports from Maddyness.
You can easily filter your search by:

- **sector**
- **announcement date range**
- **amount raised range**.

This Actor offers 2 run modes:

- **Standard run** : a one-shot search from the Actor input. Matches are pushed to the run's default dataset. This run mode gives you access to all Apify native integrations.
- **Standby** : Simple HTTP API call. Ideal when integrating from another service or spreadsheet in near real time.

Every returned startup is billed as one **pay-per-event** charge: you pay for exactly what you consume, nothing else.

### Why use Maddyness fundraising data?

- **Use funding signal for cold outreach:** Companies raising funds have more purchasing power and are therefore good targets for lead generation.
- **Market research:** Monitor trending startups and sectors.

### How to use MaddyMoney French Startup fundraising database

#### Standard run (batch)

1. Open the Actor's **Input** tab and pick your filters (any subset of sector, date range, amount range).
2. Click **Run**. Results are stored in the run's default dataset.
3. Export as JSON, CSV, HTML, or Excel from the **Storage** tab.

#### Standby API (real-time)

Simply call the [API endpoint](https://apify.com/advantageous_subcontra/maddyness-french-startup-fundraising-database/endpoints).

### Filters

All filters below apply to **both modes** — as input fields in standard mode, as query parameters in Standby mode.

| Filter | Type | Description |
|--------|------|-------------|
| `sector` | string | Case-insensitive substring match on the startup's sector tag ("biotech", "greentech", "transport / logistique", ...). Leave empty for any. |
| `announcedAtMin` | `YYYY-MM-DD` | Earliest fundraising announcement date (inclusive). |
| `announcedAtMax` | `YYYY-MM-DD` | Latest fundraising announcement date (inclusive). |
| `amountEurMin` | integer (EUR) | Minimum amount raised (inclusive). |
| `amountEurMax` | integer (EUR) | Maximum amount raised (inclusive). |
| `defaultMaxResults` (input only) | integer, 1–1000 | Default result cap. In Standby mode this is used when the caller does not pass `maxResults` on the query string. |
| `maxResults` (Standby query string only) | integer, 1–1000 | Per-request cap. **Charged per returned result.** |

#### Standby example

```bash
curl -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://<username>--maddymoney-search.apify.actor/search?sector=deeptech&announcedAtMin=2026-06-01&amountEurMin=5000000"
```

Response:

```json
{
    "count": 3,
    "totalScanned": 17,
    "results": [
        {
            "name": "Syntetica",
            "sector": "deeptech",
            "amountEur": 26200000,
            "amountRaw": "26.2 M€",
            "website": null,
            "linkedin": "https://www.linkedin.com/company/syntetica-recycle/",
            "twitter": null,
            "facebook": null,
            "instagram": null,
            "tiktok": null,
            "youtube": null,
            "websiteMarkdown": null,
            "websiteError": null,
            "maddynessProfileUrl": "https://www.maddyness.com/entreprise/syntetica/",
            "articleUrl": "https://www.maddyness.com/2026/07/17/les-startups-francaises-ont-leve-56-millions-deuros-la-semaine-derniere/",
            "articleTitle": "Les startups françaises ont levé 56 millions d'euros la semaine dernière",
            "announcedAt": "2026-07-17",
            "scrapedAt": "2026-07-30T10:17:35.977Z"
        }
    ]
}
```

Errors return HTTP 400 with `{ "error": "<field>: <reason>" }`. Missing or unreachable source dataset returns HTTP 503.

### Output

You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Every record ships with startup name, sector, amount raised in EUR (parsed) and raw, website, LinkedIn/Twitter/Facebook/Instagram/TikTok/YouTube URLs, the homepage converted to Markdown (`websiteMarkdown`), fundraising article link and title, announcement date, and scrape timestamp.

### Pricing : pay per result

This Actor uses the **pay-per-event** pricing model. Every returned startup counts as one `result` event, in both standard and standby modes.

| Event | Description | Suggested price |
|-------|-------------|-----------------|
| `result` | One matching startup returned | USD 0.0001 |

#### Tips

- **Narrow filters cost less**: a tight `amountEurMin`/`amountEurMax` range returns fewer results, so you're billed less.
- **`maxResults` is a hard cap**: set it to what you actually need, since each result is billed.
- **Sector is a substring**: `sector=tech` matches `deeptech`, `greentech`, `biotech`. Use the full tag for exact intent.

### FAQ, disclaimers, and support

**Can I combine filters?**
Yes. Any subset — even none — is accepted. All provided filters are ANDed together.

**Disclaimer**: This Actor exposes publicly-available French startup fundraising data collected from [Maddyness](https://www.maddyness.com/). It does not extract private user data.

Feedback and bug reports go to the **Issues** tab on the Actor page.

# Actor input Schema

## `sector` (type: `string`):

Restrict to startups tagged with this sector (case-insensitive substring match on the Maddyness hashtag, e.g. "biotech", "greentech", "transport / logistique"). Leave empty for any sector.

## `announcedAtMin` (type: `string`):

Earliest announcement date (inclusive), YYYY-MM-DD.

## `announcedAtMax` (type: `string`):

Latest announcement date (inclusive), YYYY-MM-DD.

## `amountEurMin` (type: `integer`):

Minimum amount raised, in whole euros (inclusive).

## `amountEurMax` (type: `integer`):

Maximum amount raised, in whole euros (inclusive).

## `defaultMaxResults` (type: `integer`):

Cap on returned results. In Standby mode this is used when the caller does not pass maxResults.

## Actor input object example

```json
{
  "sector": "biotech",
  "announcedAtMin": "2026-01-01",
  "announcedAtMax": "2026-12-31",
  "amountEurMin": 1000000,
  "amountEurMax": 50000000,
  "defaultMaxResults": 50
}
```

# 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("advantageous_subcontra/maddyness-french-startup-fundraising-database").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("advantageous_subcontra/maddyness-french-startup-fundraising-database").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 advantageous_subcontra/maddyness-french-startup-fundraising-database --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,advantageous_subcontra/maddyness-french-startup-fundraising-database"
        }
    }
}

```

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/9Mdrrepbu9y3vL1L1/builds/Jru5XBUnoiCLfupW9/openapi.json