---
title: Academic Credit System & Research SOP
description: "This page outlines our global Academic Credit System (ACS) and Standard Operating Procedure (SOP) for using PromptEasy in AI-driven research, ensuring reproducibility and compliance."
---

## 1. The Academic Credit System (ACS)

PromptEasy.EU is committed to supporting the next generation of researchers with our **Academic Credit System**. We provide **€99 in credits** to verified academic users (including both students and faculty), fully covering the **Standard Plan (€9.90/month) for ten months** at no cost.

### How to Claim Your Credits

-   **University Email**: Register using a valid university email address (e.g., from domains like `aalto.fi`, `dshs-koeln.de`, `ac-paris.fr`, or other accredited global institutions).
-   **Plan Selection**: Select the **Standard Plan** and an **Individual account** during registration to activate the credits.

> **INFO**
> **Validation Message**: Before completing registration, confirm you see this message:
> 
> > "As per our Academic Credit System policy, you are eligible for €99 worth of credits! To get these, please ensure you select Standard Plan and an Individual account."

-   **Support**: If the message doesn't appear despite using a valid university email, verify your email format and contact `support@prompteasy.eu` **before** finishing your registration.

### The Upgrade Path

-   **Flexible Credits**: You are never locked into a single tier; you can upgrade to the **Premium Plan** at any time to access advanced features.
-   **Credit Logic**: Your remaining credits automatically apply to the Premium balance. While the credit total remains the same, the duration adjusts based on the higher tier cost.
    *   *Example: If you have €50 in remaining credits and upgrade to Premium (€15/month), the credits will cover approximately 3.3 months of service.*

---

## 2. The Scientist’s SOP: Standardizing AI Research

In the scientific community, reproducibility is mandatory. This **Standard Operating Procedure (SOP)** ensures your AI-driven methodologies are as rigorous and repeatable as your laboratory work.

| Feature | Standard Plan (Level 1) | Premium Plan (Level 2) |
| :--- | :--- | :--- |
| **Focus** | Efficiency & Portability | Rigor & Accountability |
| **Key Tools** | Vault, Tokens, MCP | Version History, Audit Logs |

### Level 1: Digital Organization (Standard Plan)
*Focus: Efficiency, Portability, and Connectivity*

- **Step 1: The Sovereign Vault** – Store your research logic and data analysis prompts from private chat histories into PromptEasy.
  - *Why it matters: Preserves institutional memory and prevents data silos.*
- **Step 2: Access Tokens** – Generate a secure Access Token from your dashboard to integrate your vault with external AI agents.
  - *Why it matters: Enables secure, programmatic access to your prompts.*
- **Step 3: Discovery** – Leverage the Model Context Protocol (MCP)—our system that allows AI agents to automatically "discover" and apply your latest approved research prompts.
  - *Why it matters: Ensures agents always use the most current methodology.*

### Level 2: Scientific Rigor (Premium Plan)
*Building on basic organization, the Premium Plan adds tools for advanced accountability.*

-   **Step 4: Version History – Maintain a full history** of every change made to a prompt. 
    *   *Why it matters: Allows you to revert to the exact "Logic Layer" used in previous months to verify original experimental results.*
-   **Step 5: Audit Logs – Access a timestamped record** of every modification to your research prompts.
    *   *Why it matters: Provides a transparent "Chain of Custody" for your methodologies, essential for peer review.*

---

## 3. Integration with Academic Tools
Enhance your research workflows by incorporating PromptEasy's CSV exports and Model Context Protocol (MCP) into tools like LaTeX and Jupyter Notebooks. This section focuses on methods for integration, with concise examples.

### CSV Export Integration
Focus: Reproducible Data Handling in Publications and Analysis

Export prompts as CSV via the built-in Export feature, then import into LaTeX for formatted tables or Jupyter for interactive manipulation. CSVs include columns like Tenant Name, Vault Name, Categories, Keywords, Prompt Title, Prompt, LLM Model, LLM System Message, and LLM Settings.

#### With LaTeX: For Publication-Ready Tables
- Use packages like `csvsimple` for direct import.
- Example Code:

```latex
\documentclass{article}
\usepackage{csvsimple}

\begin{document}
\csvautotabular{your_prompts.csv}  % Auto-generates table from CSV
\end{document}
```
- Tip: Customize with `\csvreader` for alignments; use UTF-8 encoding and place CSV in project directory. For quick conversion, upload to TablesGenerator.com and copy the `tabular` snippet.

#### With Jupyter: For Interactive Exploration
- Load via `pandas` for filtering and display.
- Example Code:

```python

df = pd.read_csv('your_prompts.csv')
display(df.head())  # View table; filter e.g., df[df['Categories'] == 'Lab-Protocol-V1']
```
- Tip: Manipulate data (e.g., select prompts) and feed into AI calls; handle large files with `chunksize`. Export processed data as needed.

**Why It Matters**: CSVs enable portable, structured access to prompts for documentation or analysis, supporting open science.

### MCP Integration (All Plans with Access Token)
Focus: Programmatic Prompt Discovery and Retrieval

Use the MCP endpoint (`https://api.prompteasy.eu/v1/mcp/server`) with POST requests to list vaults, search prompt headers (encrypted content), and fetch full prompts. Authenticate via Access Token in headers (`Authorization: Bearer {token}`). Ideal for Jupyter or scripts.

**Step 1: List Vaults** – Retrieve available vaults.
- Endpoint: `POST /list_vaults` (no parameters).
- Example Code (Jupyter/Python):

```python

token = os.getenv('PROMPTEASY_TOKEN')
headers = {'Authorization': f'Bearer {token}', 'Content-Type': 'application/json'}
response = requests.post('https://api.prompteasy.eu/v1/mcp/server/list_vaults', headers=headers, json={})
vaults = response.json()  # e.g., [{'id': '12345', 'name': 'Research'}]
```

**Step 2: Search Prompts** – Find headers by query (matches keywords, title, categories).
- Endpoint: `POST /search_prompts` (parameters: `query` [required], `vault_id` [optional]).
- Example Code:

```python
payload = {'query': 'data analysis'}  # Add 'vault_id': '12345' if needed
response = requests.post('https://api.prompteasy.eu/v1/mcp/server/search_prompts', headers=headers, json=payload)
headers_list = response.json()  # e.g., [{'id': 'f4ce3c03-5c68-46dc-83c7-f030967c4016', 'title': 'Analysis Prompt', 'categories': 'data analysis, Lab-Protocol-V1'}]
```

**Step 3: Get Prompt** – Fetch full decrypted content by ID.
- Endpoint: `POST /get_prompt` (parameter: `id` [required]).
- Example Code:

```python
payload = {'id': 'f4ce3c03-5c68-46dc-83c7-f030967c4016'}
response = requests.post('https://api.prompteasy.eu/v1/mcp/server/get_prompt', headers=headers, json=payload)
prompt = response.json()  # e.g., {'prompt': 'Full prompt text...'}
```

**Step 4: Execution Example** – Chain with AI in Jupyter.
- After fetching, pass to an AI client:

```python
from openai import OpenAI

client = OpenAI()
completion = client.chat.completions.create(
    model='gpt-4',
    messages=[{'role': 'user', 'content': prompt['prompt']}]
)
print(completion.choices[0].message.content)
```
- Tip: Handle errors (e.g., invalid token); use for autonomous agent discovery.

**Why It Matters**: MCP enables secure, dynamic access to prompts in workflows, ensuring rigor without manual exports.

For MCP specs or troubleshooting, implement MCP to your AI agent and request it to evaluate MCP endpoints. PromptEasy guides AIs on endpoint usage so AI can help with coding matters.

---

## 4. Security & Sovereignty Standards

- **Zero-Knowledge Architecture**: All prompts are encrypted with military-grade **AES-256** standards. Metacode Oy has no access to your research logic—you hold the keys.
- **EU Residency**: Data centers in Belgium for low-latency EU access and to ensure full compliance with the [EU AI Act](https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai) and [GDPR](https://gdpr-info.eu/).
- **Open Source Acknowledgement**: Our domain verification relies on the open-source [University Domains List](https://github.com/Hipo/university-domains-list) project for accurate academic email validation.

---

### Ready to get started?
**[Register now for your Academic Credits](https://prompteasy.eu/signup.md)**