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mcp-gladia

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mcp-gladia

MCP server for Gladia audio transcription and intelligence. Enables LLMs to transcribe, analyze, and translate audio/video content through Gladia's API.

Getting Your API Key

  1. Sign up at app.gladia.io

  2. Navigate to the API Keys section

  3. A default API key is automatically created for new accounts

Gladia offers 10 hours of free audio transcription per month. No credit card required.

Related MCP server: Deepgram MCP Server

Installation

npm install mcp-gladia

Or run directly:

npx mcp-gladia

Configuration

Set your Gladia API key as an environment variable:

export GLADIA_API_KEY=your-api-key-here

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "gladia": {
      "command": "npx",
      "args": ["mcp-gladia"],
      "env": {
        "GLADIA_API_KEY": "your-api-key-here"
      }
    }
  }
}

Claude Code

claude mcp add gladia -- npx mcp-gladia

Then set your API key in the environment or .env file.

Other MCP Clients

Any MCP-compatible client can use this server via stdio transport. Set the command to npx mcp-gladia and provide GLADIA_API_KEY as an environment variable.

Tools

upload_file

Upload an audio/video file to Gladia for transcription.

Parameter

Type

Required

Description

filePath

string

Yes

Path to the audio/video file

Supported formats: mp3, wav, m4a, mp4, mov, avi, flac (max 1GB).

transcribe

Submit an audio file for transcription with automatic polling until completion. Supports all Gladia audio intelligence features. Returns the completed result or a job ID if timeout occurs (5 min).

Parameter

Type

Required

Description

audioUrl

string

Yes

URL from upload_file

language

string

No

Language code (e.g. en, fr). See supported languages

detectLanguage

boolean

No

Auto-detect language (default: true)

diarization

boolean

No

Enable speaker identification

diarizationConfig

object

No

{ numberOfSpeakers?, minSpeakers?, maxSpeakers? }

subtitles

boolean

No

Generate subtitle files

subtitlesConfig

object

No

{ formats: ["srt", "vtt"] }

customVocabulary

string[]

No

Custom words to improve recognition

summarization

boolean

No

Enable transcription summary

summarizationConfig

object

No

{ type: "general" | "concise" | "bullet_points" }

sentimentAnalysis

boolean

No

Enable sentiment/emotion analysis

namedEntityRecognition

boolean

No

Enable entity detection

chapterization

boolean

No

Enable chapter detection with timestamps

translation

boolean

No

Enable translation

translationConfig

object

No

{ targetLanguages: ["fr", "es"], model?: "base" | "enhanced" }

audioToLlm

boolean

No

Enable custom LLM analysis

audioToLlmConfig

object

No

{ prompts: ["your question about the audio"] }

get_transcription_status

Check the status of a transcription job (useful for long-running jobs that timed out).

Parameter

Type

Required

Description

jobId

string (UUID)

Yes

Job ID from a previous transcribe request

list_transcription_jobs

List past transcription jobs with optional filtering.

Parameter

Type

Required

Description

offset

number

No

Pagination offset

limit

number

No

Max results (default: 20)

status

string

No

Filter: queued, processing, done, error

afterDate

string

No

Filter by creation date (ISO 8601)

beforeDate

string

No

Filter by creation date (ISO 8601)

kind

string

No

Filter: pre-recorded, live

delete_transcription_job

Delete a transcription job and its data.

Parameter

Type

Required

Description

jobId

string (UUID)

Yes

Job ID to delete

Audio Intelligence Features

All intelligence features are enabled as options on the transcribe tool and processed server-side by Gladia.

Summarization

Generate a summary of the transcription in one of three formats:

Type

Description

general

Balanced, comprehensive summary (default)

concise

Short overview of key points

bullet_points

Key takeaways as a bullet list

{ "summarization": true, "summarizationConfig": { "type": "bullet_points" } }

Sentiment & Emotion Analysis

Detect sentiment and emotion for each sentence in the transcript, with speaker attribution when diarization is enabled.

Sentiments: positive, negative, neutral, mixed, unknown

Emotions: adoration, anger, joy, fear, surprise, sadness, neutral, and more

{ "sentimentAnalysis": true }

Named Entity Recognition

Detect and classify entities mentioned in the audio. Supports 50+ entity types across multiple categories:

Category

Entity Types

PII

Name, Email, Phone Number, SSN

Location

City, Country, Address

Medical (PHI)

Conditions, Drugs, Injuries

Financial

Bank Account, Credit Card

Demographic

Age, Gender, Occupation

Temporal

Date, Time

Supports GDPR, HIPAA, and CPRA compliance workflows.

{ "namedEntityRecognition": true }

Chapterization

Automatically segment audio into logical chapters. Each chapter includes:

  • Summary — overview of the chapter content

  • Headline — short title

  • Gist — one-line bottom line

  • Keywords — key terms mentioned

  • Timestamps — start and end times

{ "chapterization": true }

Translation

Translate transcriptions to one or more target languages.

Model

Description

base

Fast translation, covers most use cases

enhanced

Higher quality, better for complex content

{ "translation": true, "translationConfig": { "targetLanguages": ["fr", "es"], "model": "enhanced" } }

Audio-to-LLM (Custom Prompts)

Run custom analysis prompts directly against the audio content. No need to post-process transcripts with a separate LLM.

{
  "audioToLlm": true,
  "audioToLlmConfig": {
    "prompts": [
      "Extract the key decisions made in this meeting",
      "What are the action items and who is responsible?"
    ]
  }
}

Speaker Diarization

Identify and separate speakers in the audio. Output includes speaker labels on every utterance.

{
  "diarization": true,
  "diarizationConfig": { "minSpeakers": 2, "maxSpeakers": 5 }
}

Supported Languages

100+ languages supported for transcription. Use the language code with the language parameter, or set detectLanguage: true (default) for automatic detection.

Language

Code

Language

Code

Language

Code

Afrikaans

af

Hawaiian

haw

Persian

fa

Albanian

sq

Hebrew

he

Polish

pl

Amharic

am

Hindi

hi

Portuguese

pt

Arabic

ar

Hungarian

hu

Punjabi

pa

Armenian

hy

Icelandic

is

Romanian

ro

Assamese

as

Indonesian

id

Russian

ru

Azerbaijani

az

Italian

it

Sanskrit

sa

Bashkir

ba

Japanese

ja

Serbian

sr

Basque

eu

Javanese

jw

Shona

sn

Belarusian

be

Kannada

kn

Sindhi

sd

Bengali

bn

Kazakh

kk

Sinhala

si

Bosnian

bs

Khmer

km

Slovak

sk

Breton

br

Korean

ko

Slovenian

sl

Bulgarian

bg

Lao

lo

Somali

so

Catalan

ca

Latin

la

Spanish

es

Chinese

zh

Latvian

lv

Sundanese

su

Croatian

hr

Lingala

ln

Swahili

sw

Czech

cs

Lithuanian

lt

Swedish

sv

Danish

da

Luxembourgish

lb

Tagalog

tl

Dutch

nl

Macedonian

mk

Tajik

tg

English

en

Malagasy

mg

Tamil

ta

Estonian

et

Malay

ms

Tatar

tt

Faroese

fo

Malayalam

ml

Telugu

te

Finnish

fi

Maltese

mt

Thai

th

French

fr

Maori

mi

Tibetan

bo

Galician

gl

Marathi

mr

Turkish

tr

Georgian

ka

Mongolian

mn

Turkmen

tk

German

de

Myanmar

my

Ukrainian

uk

Greek

el

Nepali

ne

Urdu

ur

Gujarati

gu

Norwegian

no

Uzbek

uz

Haitian Creole

ht

Nynorsk

nn

Vietnamese

vi

Hausa

ha

Occitan

oc

Welsh

cy

Pashto

ps

Wolof

wo

Yiddish

yi

Yoruba

yo

Usage Examples

Basic Transcription

Upload my-recording.mp3 and transcribe it

Meeting with Multiple Speakers

Transcribe this meeting recording with diarization enabled, expecting 3-5 speakers.
Generate a bullet-point summary and extract action items using audio-to-LLM.

Multilingual Content Analysis

Transcribe this podcast, detect the language, translate to English and French,
and run sentiment analysis on the conversation.

Compliance & Entity Detection

Transcribe this customer call with named entity recognition to identify
any PII mentioned (names, emails, phone numbers).

Custom Audio Analysis

Transcribe this earnings call and use audio-to-LLM with these prompts:
- "What are the key financial metrics mentioned?"
- "What is the company's guidance for next quarter?"
- "Summarize the Q&A section"

Troubleshooting

Issue

Solution

GLADIA_API_KEY is required

Set the GLADIA_API_KEY environment variable

Unsupported file format

Use mp3, wav, m4a, mp4, mov, avi, or flac

File too large

Files must be under 1GB

Transcription timeout

Use get_transcription_status with the returned job ID

Translation fails

Ensure translationConfig.targetLanguages is provided

Invalid uuid

Job IDs must be valid UUIDs (from transcribe or list_transcription_jobs)

Development

git clone https://github.com/gladiaio/mcp-gladia.git
cd mcp-gladia
npm install
npm run build
npm run dev

Requires Node.js 18+.

Links

License

MIT

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