Name: OpenTranscribe MCP
Author: fbossiere

OpenTranscribe MCP turns recorder audio into a provider-independent transcript

Own the recorder. Choose the intelligence.

OpenTranscribe is an open-source MCP server that routes audio to the speech-to-text model of your choice and returns one provider-independent transcript schema.

It is built around a simple idea: buying a great recorder should not lock you into one transcription subscription. Use Plaud, a phone, an open-source wearable, or any other audio source you are authorized to access, then choose Microsoft MAI, ElevenLabs Scribe, or Groq Whisper without changing the downstream workflow.

OpenTranscribe does not jailbreak hardware or bypass access controls. It works only with audio the operator is authorized to access.

How it works

Audio flows from a recorder through OpenTranscribe MCP and a selectable speech-to-text provider into one canonical transcript schema for downstream workflows

OpenTranscribe keeps the integration boundary stable: the recorder supplies an audio file or HTTPS URL, the server selects or calls the requested speech-to-text provider, and downstream tools receive the same canonical transcript shape.

What v1 ships

MCP Streamable HTTP at /mcp, with stateless operation and bearer or external OIDC authentication
transcribe_audio, list_transcription_models, estimate_transcription_cost, get_transcript_chunk, and delete_transcript
Microsoft MAI-Transcribe-2, ElevenLabs scribe-v2, and Groq Whisper adapters
explicit capability negotiation, routing policies, retries, and observable fallbacks
HTTPS URL passthrough when supported and a bounded streaming proxy otherwise
SSRF controls, signed-URL redaction, zero content logging, and cost/resource limits
disabled-by-default retention; optional memory or S3-compatible temporary result storage
Docker, production-oriented Scaleway Serverless Containers Terraform, tests, and GitHub Actions CI

On the Linux desktop

An optional Debian package, OpenTranscribe Setup, bundles the Python runtime, the engine, and a native setup application. Install it, add a provider key, and connect a local MCP client — no Python, no uv, no configuration files. The engine then runs as one client-owned STDIO process that opens no network socket.

The hosted and command-line paths below are unaffected by it. See OpenTranscribe Setup on Linux; its release evidence lives in docs/desktop-acceptance.md, where every scenario starts at Not tested.

Ten-minute quickstart

Requirements: Python 3.12 and uv, or Docker.

bash

git clone https://github.com/fbossiere/open-transcribe-mcp.git
cd open-transcribe-mcp

Create a private .env containing only the settings for your selected provider and a strong random MCP bearer token. For Microsoft:

dotenv

OT_ENVIRONMENT=prod
OT_HOST=127.0.0.1
OT_DEFAULT_PROVIDER=microsoft
OT_DEFAULT_MODEL=MAI-Transcribe-2
OT_MICROSOFT__ENDPOINT=https://YOUR-RESOURCE.cognitiveservices.azure.com
OT_MICROSOFT__API_KEY=YOUR-KEY
OT_SECURITY__AUTH_MODE=bearer
OT_SECURITY__BEARER_TOKEN=YOUR-RANDOM-TOKEN

Use the complete Groq, ElevenLabs or multi-provider recipes for other services. Omit unused settings rather than leaving empty URLs or numbers from .env.example, which is a configuration inventory. Protect your file with chmod 600 .env.

Start the server:

bash

uv sync
uv run open-transcribe-mcp

The MCP endpoint is http://localhost:8000/mcp; probes are available at /healthz and /readyz.

Run the included bilingual, two-voice synthetic recording through the connected provider:

bash

uv run python examples/transcribe.py --token YOUR-RANDOM-TOKEN

The fixture and reference transcript are non-sensitive and redistributable. Pass another authorized public HTTPS audio URL as the first argument to use your own source.

Connect a FastMCP client:

python

import asyncio
from fastmcp import Client


async def main() -> None:
    async with Client("http://localhost:8000/mcp", auth="YOUR-RANDOM-TOKEN") as client:
        models = await client.call_tool("list_transcription_models", {})
        print(models)
        result = await client.call_tool(
            "transcribe_audio",
            {
                "request": {
                    "source": {"type": "url", "url": "https://example.org/authorized-audio.mp3"},
                    "provider": "auto",
                    "routing_policy": "quality",
                }
            },
        )
        print(result)


asyncio.run(main())

Provider choice does not alter the response contract. Set provider and model to switch explicitly, or use auto with default, quality, cost, or latency routing.

diarization, timestamps, and transcript_style are unset above on purpose: an unset capability is not requested, so the request routes to any configured model and the response metadata reports what that model applied. Stating one makes it a requirement — "diarization": True excludes every model that cannot diarize rather than quietly returning a single-speaker transcript. See providers and capabilities.

Docker

Use the published image and the private environment file from the quickstart:

bash

docker run --rm --env-file .env \
  -e OT_ENVIRONMENT=prod -e OT_HOST=0.0.0.0 \
  -p 127.0.0.1:8000:8000 \
  ghcr.io/fbossiere/open-transcribe-mcp:1.2.1

This binds the host port locally; put an HTTPS proxy in front when hosting remotely. You can also build from source with docker build -t open-transcribe-mcp:1.2.1 .. Inject provider credentials at runtime. The image includes the s3 extra, but result storage stays disabled unless configured.

Deploy on Scaleway

The reference infra/scaleway module provisions a private image registry, a Serverless Container with scale-to-zero (0–3 instances), HTTPS ingress and health probes. It can optionally add a TTL-bound result bucket and runtime identity.

Create a dedicated Scaleway Project and a deployment API key with the documented IAM permissions. Supply SCW_ACCESS_KEY and SCW_SECRET_KEY to the deployment shell.
Copy infra/scaleway/terraform.tfvars.example to terraform.tfvars in that directory. Fill your project ID, provider keys, authentication settings and image_tag = "1.2.1". The template configures ElevenLabs and Groq; review the ElevenLabs retention choice before use.

Bootstrap the registry, copy the public release image into it, then review and apply the complete deployment. In infra/scaleway:

bash

terraform init
terraform apply -target=scaleway_registry_namespace.this
IMAGE_REFERENCE="$(terraform output -raw image_reference)"
REGISTRY_ENDPOINT="$(terraform output -raw registry_endpoint)"
printf '%s' "$SCW_SECRET_KEY" | docker login "${REGISTRY_ENDPOINT%%/*}" \
  --username nologin --password-stdin
docker buildx imagetools create --tag "$IMAGE_REFERENCE" \
  ghcr.io/fbossiere/open-transcribe-mcp:1.2.1
terraform plan -out=open-transcribe.tfplan
terraform apply open-transcribe.tfplan
terraform output -raw mcp_endpoint

Check /healthz, /readyz, MCP authentication and one short authorized transcription. The full Scaleway guide covers release digest verification, adoption of an existing deployment, OIDC setup, upgrades, rollback and result-store permissions.

Bootstrap applies are for new infrastructure. Import an existing registry, namespace and container into state first to preserve their IDs and endpoint. Keep real terraform.tfvars, state and saved plans private: state and plans can contain secrets even when output is redacted. Publishing a release does not automatically update your Scaleway deployment.

Configuration and service combinations

Choose the provider, MCP authentication and result storage independently. Provider keys stay on the server and are never accepted as tool arguments. See the full configuration guide for complete environment/Terraform examples, settings precedence, key permissions and troubleshooting.

Transcription services	Configuration	Use and limitations
Microsoft only	Microsoft endpoint + key; defaults `microsoft` / `MAI-Transcribe-2`	Diarization and clean/verbatim output
ElevenLabs only	ElevenLabs key; defaults `elevenlabs` / `scribe-v2`	Diarization; choose eligible zero retention or explicitly accepted standard mode
Groq only	Groq key; defaults `groq` / a Whisper model	Verbatim transcription; no speaker diarization
Multiple providers	Each provider's credentials; one matching default pair	Requests can select any configured provider; compatibility is checked before ranking

OT_DEFAULT_PROVIDER and OT_DEFAULT_MODEL are preferences, not a provider allow-list. An explicit request can choose another configured model. Hosted requests permit transient fallback by default; use allow_fallback=false when audio must go to only one provider. To require French speaker turns, use language=fr, diarization=true and strict_capabilities=true; see the Scribe recipe. Groq cannot fulfill that requirement and is rejected rather than silently returning an undiarized transcript.

Authentication / storage	Required configuration	Combination rules
HTTP bearer	MCP token; Terraform `auth_mode = "bearer"`	Works with any provider; token is separate from provider keys
HTTP OIDC	Issuer, JWKS, service origin, scope and entitlement; `auth_mode = "oidc"`	Works with any provider; use an external identity provider such as Keycloak
Managed desktop STDIO	Setup TOML and Secret Service keyring	Local process authentication; enable providers and privacy permissions in Setup
No result store	Default `disabled`; Terraform `enable_result_store = false`	Inline output; stored or oversized auto results fail explicitly
Temporary S3 results	Cursor secret; Terraform `enable_result_store = true`	Shared chunks across instances, TTL and deletion; extra IAM permissions required
Memory results	`OT_RESULT_STORE__BACKEND=memory` + cursor secret	Local/test only; unsuitable for Scaleway cold starts or multiple instances

ElevenLabs requests default to zero retention, which needs an eligible Enterprise account. A standard account requires an explicit choice of OT_ELEVENLABS__ZERO_RETENTION=false after accepting provider-side retention. Disabling OpenTranscribe storage does not disable provider retention. See configuration and retention.

For ordinary HTTP, OT_* environment variables override a working-directory .env. Terraform injects the non-secret and secret maps from your private tfvars, while enforcing production security settings. Managed desktop mode ignores ambient environment settings; a key in the keyring does not enable a provider by itself. Changing keys/defaults needs a restart or Terraform apply, not a new application image. A new application version needs a published image and a separate deployment update.

Publication and upgrades

The publication protocol is the maintainer runbook: semantic versioning, version coherence, local checks, release PR, signed tag from reviewed main, automated publication, artifact verification and recovery after partial failure.

Git tags use v1.2.1; Python/MCP metadata and image tags use 1.2.1. The workflow publishes PyPI, the MCP Registry, GHCR and the Linux package, then creates an immutable GitHub release with checksums and provenance. Each deployment chooses its own version and configuration. For Scaleway upgrades, copy the chosen release into the private registry, update image_tag (and the release digest when pinned), review the plan, apply and verify the endpoint.

Security and privacy defaults

source HTTPS is required;
private, loopback, link-local, multicast, reserved, and metadata destinations are rejected;
every redirect target is resolved and validated;
proxy downloads connect to the validated public IP while preserving HTTPS SNI and the original Host header;
source downloads are streamed to an ephemeral file with byte limits, then deleted;
signed URL queries, audio, transcript text, authorization headers, and phrase hints are not logged;
no project telemetry is emitted;
transcripts are not retained unless a result store is explicitly enabled and used.
ElevenLabs zero-retention requests are enabled by default; disabling them is an explicit operator choice.

Read SECURITY.md, the threat model, and the retention policy before exposing the service publicly.

Known limitations

OpenTranscribe currently targets self-hosted, single-tenant installations. Provider feature parity is deliberately not guaranteed; capability negotiation exposes differences instead of hiding them. URL ingestion is the only remote input type. Synchronous provider limits still apply. OIDC supports external identity providers; asynchronous jobs remain a future capability. The memory store is neither durable nor horizontally scalable. S3 lookups prioritize a simple deployment contract over very-large-bucket indexing; dedicate the result prefix and enforce lifecycle deletion.

Application controls do not replace network policy. Internet-facing operators should still combine exact source-host allow-listing with egress firewall rules.

Provider prices, APIs, and capabilities change. The checked-in metadata is informational, not a contractual quote.

The desktop package targets Ubuntu 24.04 LTS on amd64 and is not yet supported on any other release, desktop, or architecture. No MCP client has a recorded end-to-end registration run, so OpenTranscribe Setup presents automatic registration as untested and verifies it by reading the registration back.

OpenTranscribe processes audio supplied by the operator. Recording and transcribing people may be subject to consent, privacy, employment, telecommunications, or data-protection laws. Operators are responsible for ensuring they have the necessary rights and consent.

Transcript content is untrusted data. OpenTranscribe never interprets it as instructions; downstream agents must preserve the same boundary.

Documentation

The canonical documentation site is fbossiere.github.io/open-transcribe-mcp.

Contributing

Contributions are welcome. Start with the contribution guide; open a feature issue before substantial work, and report vulnerabilities only through the private process in SECURITY.md.

Independence and trademarks

OpenTranscribe is an independent open-source project maintained by its contributors. It is not affiliated with, endorsed by, or sponsored by Plaud, Microsoft, ElevenLabs, Groq, or any transcription provider.

Plaud and all provider product names are trademarks of their respective owners.