Email, headers to attachments, one call.

From/To/Subject headers, the message body, and attached documents — extracted together, not as separate steps you have to orchestrate.

the-problem

Email is a container format wearing a text format's clothes: headers, a MIME-encoded body (often both plain-text and HTML parts), and arbitrary attached documents that themselves need extracting. Most extraction tools — especially VLM-based ones built around single images or pages — simply don't have an email code path at all, leaving teams to hand-roll header parsing and MIME decoding just to get to 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 — same request shape as every other format.

curl
curl -X POST https://api.txtfetch.com/v1/extract \
  -H "Authorization: Bearer $TXTFETCH_KEY" \
  -F file=@support-thread.eml
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
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
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 -X POST "https://api.txtfetch.com/v1/extract?url=https://example.com/archive/2024-q1.mbox" \
  -H "Authorization: Bearer $TXTFETCH_KEY"
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
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
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": "..."
}

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, ready to feed into a prompt or embedding step.
Does it support Outlook .msg files?
Yes — same endpoint, same response shape. Under the hood .msg is a completely different container (OLE2 with MAPI property streams, not RFC-822), so it's worth reading 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 folded into the response alongside the message body.

go-further

Email

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