# Token Intel Report (`roosterk16/token-intel-report`) Actor

Token intelligence reports for Base tokens: market data, on-chain overview, sentiment & risk flags. Real-time research, ~90 second delivery.

- **URL**: https://apify.com/roosterk16/token-intel-report.md
- **Developed by:** [Felipe Gallo](https://apify.com/roosterk16) (community)
- **Categories:** AI
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 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/platform/actors/running/actors-in-store#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

## Token Intel Report

Get a structured **token intelligence report** for any token on Base (or other EVM chains): real-time web research condensed into a professional due-diligence brief, in clean Markdown.

### What you get

Every run produces a ~700–900 word report with five sections:

1. **Snapshot** — ticker, contract address, category, price / market cap / FDV / volume (verified where possible)
2. **On-Chain Overview** — holder concentration, liquidity, supply, emissions and unlocks
3. **Sentiment & Narrative** — current sentiment, recent news and catalysts, narrative positioning
4. **Risk Flags** — concrete, token-specific risks (not generic boilerplate)
5. **Bottom Line** — bullet summary with a qualitative stance and confidence level

Reports are grounded in web research retrieved at run time and dated ("as of YYYY-MM-DD"). Figures that can't be verified are explicitly marked "unverified" — no invented numbers. This is research, not financial advice.

### Input

| Field | Required | Description |
|---|---|---|
| `token` | ✔ | Token symbol, name or contract address (e.g. `VIRTUAL`, `AERO`, `0x...`) |
| `contractAddress` | | Contract address, if known |
| `chain` | | Chain (default: Base) |
| `notes` | | Extra focus, e.g. "focus on unlock schedule" |

### Output

The report lands in the run's **dataset** (`report` field, Markdown) and as `report.md` in the key-value store. Typical delivery time: 60–120 seconds.

### Pricing

Pay-per-event: you're charged once per successfully delivered report. **If generation fails, you are not charged.**

### Who runs this

The same engine also serves paying agents on the Virtuals Protocol ACP (agent: RoosterIntelPro) and via an x402-paywalled HTTP endpoint — this Actor is the Apify packaging of a production service.

# Actor input Schema

## `token` (type: `string`):

Token symbol, name or contract address to research (e.g. VIRTUAL, AERO, 0x...)

## `contractAddress` (type: `string`):

Token contract address, if known

## `chain` (type: `string`):

Chain the token lives on (default: Base)

## `notes` (type: `string`):

Any extra focus for the report (e.g. 'focus on unlock schedule')

## Actor input object example

```json
{
  "chain": "Base"
}
```

# Actor output Schema

## `report` (type: `string`):

Dataset items containing the generated report: token, chain, report (Markdown), model, generatedAt

## `reportMarkdown` (type: `string`):

The raw report.md file from the key-value store

# 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("roosterk16/token-intel-report").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("roosterk16/token-intel-report").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 roosterk16/token-intel-report --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,roosterk16/token-intel-report"
        }
    }
}

```

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/HTASbeEysVVnG8Spp/builds/bBZRNYXjGcEmcCkej/openapi.json