io.github.pablixnieto2/etld-mcp-server
Deterministic B2B Data Middleware. Waterfall parsing for CSV, EDI, SEC & Finance. No hallucinations.
Open source Open in the app JSON README (API)
About
Deterministic B2B Data Middleware. Waterfall parsing for CSV, EDI, SEC & Finance. No hallucinations.
Details
- Kind
- MCP servers
- Topic
- Files & documents
- Publisher
- pablixnieto2
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 3.2.2
- Stars
- 2
- Last push
- 2026-03-26T21:42:52Z
- Repository state
- ativo
- Language
- JavaScript
- Added
- 2026-08-29 04:00:58
- Updated
- 2026-08-29 04:00:58
- Origin id
io.github.pablixnieto2/etld-mcp-server
README
# ETL-D MCP Server 🌊
[](https://www.npmjs.com/package/etld-mcp-server)
[](https://pypi.org/project/etld/)
[](https://registry.modelcontextprotocol.io/pablixnieto2/etld-mcp-server)
[](https://opensource.org/licenses/MIT)
**ETL-D** is a deterministic data middleware designed to act as a shield for AI Agents. It stops LLMs from "hallucinating" over structured data by providing a strict, 3-layer parsing architecture via the Model Context Protocol (MCP).
## ⚠️ The Problem: The "Data Tax" & Hallucinations
Standard LLMs are terrible at reading raw B2B files (CSV, PDF, EDI, Norma 43). They suffer from:
1. **Token Exhaustion:** Sending a 5,000-row CSV to context is a waste of money.
2. **Precision Loss:** LLMs struggle with spatial alignment. A misplaced comma in a bank statement is a financial catastrophe.
3. **Non-Determinism:** You can't build a reliable pipeline if the output format depends on the LLM's "mood."
## ✅ The Solution: 3-Layer Waterfall Architecture
The ETL-D engine processes every request through a strict hierarchy:
* **Layer 1 (Heuristic):** 100% Python-native deterministic parsers. 0% Hallucination risk. ~70ms latency.
* **Layer 2 (Semantic):** Column-to-Schema alignment using embedding-based routing.
* **Layer 3 (LLM Shield):** Strict JSON enforcement using Llama 3.3 70B with `additionalProperties: false` constraints for high-entropy noise.
---
## 🚀 Quick Start (Claude Desktop)
1. Open your `claude_desktop_config.json`.
2. Add the **ETL-D** server (Ensure you use version `3.3.3`):
```json
{
"mcpServers": {
"etld": {
"command": "npx",
"args": [
"-y",
"@pablixnieto2/etld-mcp-server@3.3.3"
],
"env": {
"ETLD_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}
```
## 🔑 How to Get an API Key?
* **Option A:** Manual Purchase (Human)
Get a Starter Pack ($5 / 5,000 credits) or a Subscription at api.etl-d.net.
* **Option B:** Zero-Touch Provisioning (Agent-Led) 🤖
If you don't have a key, simply ask Claude: "I don't have an ETL-D key, can you help me get one?".
The agent will call the /provision tool, generate a Stripe Checkout link for you, and automatically set up the key once paid. Zero-touch, human-in-the-loop.
## 🛠️ Available MCP Tools
1. Financial & B2B Heavy Lifting
parse_bank_statement: Support for Spanish Norma 43 (N43). Turns raw bank files into clean JSON.
parse_trade_history: Deterministic extraction of trades, fees, and dividends from complex broker exports.
parse_edi: ANSI X12 EDI parser (Optimized for 850 Purchase Orders).
generate_sepa_xml: JSON to PAIN.008 (Direct Debit) XML generator.
2. Document Intelligence
pdf_to_spatial_markdown: Crucial for Agents. Converts PDFs to Markdown preserving table structures before the LLM reads them.
extract_invoice / extract_resume: High-accuracy schema extraction for standard B2B documents.
3. Atomic Enrichment (1 Credit/call)
enrich_amount: Cleans "Total: 1.240,50€" into {amount: 1240.50, currency: "EUR"}.
enrich_date: Resolves human-readable dates ("next Friday at 5pm") with Timezone awareness.
enrich_address: Standardizes global messy addresses into structured components.
accounting_map: Maps concepts to ES PGC, US GAAP, or IFRS.
## 🏗️ Ecosystem
Cloud Engine: Hosted at api.etl-d.net (Python/FastAPI).
Python SDK: pip install etld.
n8n Nodes: Available in the n8n community as n8n-nodes-etld.
## ⚖️ License
MIT - Created by Pablixnieto2