> Source: https://txtfetch.com/extract/email
> Plain-text twin — every page on txtfetch.com has one. https://txtfetch.com/text

---

# Email, headers to attachments, one call.

From/To/Subject headers, the message body, and attached documents all come out together. You don't orchestrate separate steps.

the-problem

Email is a container format wearing a text format's clothes. It has headers, a MIME-encoded body (often both plain-text and HTML parts), and arbitrary attached documents that themselves need extracting. Most extraction tools have no email code path at all. That's especially true for VLM-based tools built around single images or pages. Teams end up hand-rolling header parsing and MIME decoding just to get the text they actually want.

one-request-solution

txtfetch treats email as a first-class format. POST an .eml, Outlook .msg, or .mbox archive, and Apache Tika extracts headers, body, and attachment text together into one plain-text response. The request shape is the same as every other format.

curl

```curl
curl -X POST https://api.txtfetch.com/v1/extract \
  -H "Authorization: Bearer $TXTFETCH_KEY" \
  -F file=@support-thread.eml
```

Python

```python
import os
import requests

with open("support-thread.eml", "rb") as f:
    r = requests.post(
        "https://api.txtfetch.com/v1/extract",
        headers={"Authorization": f"Bearer {os.environ['TXTFETCH_KEY']}"},
        files={"file": f},
    )

print(r.json()["extracted_text"])
```

JavaScript

```javascript
import { readFile } from "node:fs/promises";

const file = new Blob([await readFile("support-thread.eml")]);
const form = new FormData();
form.append("file", file, "support-thread.eml");

const res = await fetch("https://api.txtfetch.com/v1/extract", {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.TXTFETCH_KEY}` },
  body: form,
});

const { extracted_text } = await res.json();
console.log(extracted_text);
```

Go

```go
package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"mime/multipart"
	"net/http"
	"os"
)

type extractResponse struct {
	Status        string `json:"status"`
	ExtractedText string `json:"extracted_text"`
}

func main() {
	f, err := os.Open("support-thread.eml")
	if err != nil {
		panic(err)
	}
	defer f.Close()

	var body bytes.Buffer
	writer := multipart.NewWriter(&body)
	part, err := writer.CreateFormFile("file", "support-thread.eml")
	if err != nil {
		panic(err)
	}
	if _, err := io.Copy(part, f); err != nil {
		panic(err)
	}
	writer.Close()

	req, err := http.NewRequest("POST", "https://api.txtfetch.com/v1/extract", &body)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("TXTFETCH_KEY"))
	req.Header.Set("Content-Type", writer.FormDataContentType())

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	var result extractResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		panic(err)
	}
	fmt.Println(result.ExtractedText)
}
```

Or skip the download. Pass a `url` parameter and txtfetch fetches the document server-side:

curl

```curl
curl -X POST "https://api.txtfetch.com/v1/extract?url=https://example.com/archive/2024-q1.mbox" \
  -H "Authorization: Bearer $TXTFETCH_KEY"
```

Python

```python
import os
import requests

r = requests.post(
    "https://api.txtfetch.com/v1/extract",
    headers={"Authorization": f"Bearer {os.environ['TXTFETCH_KEY']}"},
    params={"url": "https://example.com/archive/2024-q1.mbox"},
)

print(r.json()["extracted_text"])
```

JavaScript

```javascript
const endpoint = new URL("https://api.txtfetch.com/v1/extract");
endpoint.searchParams.set("url", "https://example.com/archive/2024-q1.mbox");

const res = await fetch(endpoint, {
  method: "POST",
  headers: { Authorization: `Bearer ${process.env.TXTFETCH_KEY}` },
});

const { extracted_text } = await res.json();
console.log(extracted_text);
```

Go

```go
package main

import (
	"encoding/json"
	"fmt"
	"net/http"
	"net/url"
	"os"
)

type extractResponse struct {
	Status        string `json:"status"`
	ExtractedText string `json:"extracted_text"`
}

func main() {
	endpoint, err := url.Parse("https://api.txtfetch.com/v1/extract")
	if err != nil {
		panic(err)
	}
	q := endpoint.Query()
	q.Set("url", "https://example.com/archive/2024-q1.mbox")
	endpoint.RawQuery = q.Encode()

	req, err := http.NewRequest("POST", endpoint.String(), nil)
	if err != nil {
		panic(err)
	}
	req.Header.Set("Authorization", "Bearer "+os.Getenv("TXTFETCH_KEY"))

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer resp.Body.Close()

	var result extractResponse
	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
		panic(err)
	}
	fmt.Println(result.ExtractedText)
}
```

```
{
  "status": "success",
  "extracted_text": "..."
}
```

what-comes-back

That is the shape. This is the text. A real .eml from the benchmark corpus, word-diffed against the raw parser output. Nothing here was written for this page. Every character comes from a committed fixture.

Invoice Follow-up (EML)

`invoice-followup.eml` · message/rfc822 · left pane read via Apache Tika, **right pane: the human-checked expected.json**

raw parser output

```
From: Priya Shah <priya@example.com>
To: Billing <billing@example.com>
Subject: Re: Invoice #7734

Hi team,

Following up on the invoice below — could you confirm receipt?

Description	Qty	Amount
Consulting hours	12	$1,800.00
Travel	1	$340.00

Invoice total: $2,140.00
Due date: 2026-08-15

Thanks,
Priya
```

the human-checked ideal

```
From: Priya Shah <priya@example.com>

To: Billing <billing@example.com>

Subject: Re: Invoice #7734

Hi team,

Following up on the invoice below — could you confirm receipt?

Description	Qty	Amount
Consulting hours	12	$1,800.00
Travel	1	$340.00

Invoice total: $2,140.00
Due date: 2026-08-15

Thanks, Priya
```

[See all ten documents, with the full explanation →](https://txtfetch.com/diff)

formats-covered

-   `.eml`
-   `.msg`
-   `.mbox`

faq

**Can I parse a .eml email for an LLM?**: Yes. POST the .eml file to https://api.txtfetch.com/v1/extract and get back headers, body, and any attachment text as one plain-text response. It's ready to feed into a prompt or embedding step.

**Does it support Outlook .msg files?**: Yes, through the same endpoint, with the same response shape. Under the hood, .msg is a completely different container: OLE2 with MAPI property streams, not RFC-822. Read the dedicated .msg page if you're debugging attachment or nesting behavior.

**Can it process a whole .mbox archive?**: Yes. Apache Tika reads .mbox archives and extracts the contained messages' text.

**Are email attachments included in the extracted text?**: Yes. Attached documents are parsed, and their text is folded into the response alongside the message body.

go-further

-   [Outlook .msg internals, .pst/.ost, and nested attachments →](https://txtfetch.com/extract/msg)
-   [Drop a real .eml or .msg and see the extracted text, free →](https://txtfetch.com/tools/email-to-text)
-   [API quickstart →](https://txtfetch.com/docs)
-   [How the pipeline works →](https://txtfetch.com/how-it-works)
-   [Extract it from your language →](https://txtfetch.com/for)
-   [Get an API key →](https://app.txtfetch.com/signup)

Email

-   [`.msg`](https://txtfetch.com/extract/msg)
-   [All formats →](https://txtfetch.com/extract)

## Send a real .eml through it.

One HTTP call returns the text. Read one in your browser first, for free.

[Get an API key →](https://app.txtfetch.com/signup)

[Open the free .eml reader →](https://txtfetch.com/tools/email-to-text)