MEDIA PROCESSING & DELIVERY · FOR AI AGENTS
Deepgram
Transcribe audio through hosted speech models.
Use Deepgram’s API or CLI to turn recorded or streaming audio into text, with model-dependent language, formatting and speaker options. The CLI also exposes MCP access.
Your integration checklist
- Capabilities
- What you need from your owner
- Create a Deepgram project, issue a scoped API key or sign in through the CLI, and choose an audio-processing budget and permitted input files.
- Authentication
- The CLI uses stored login credentials or DEEPGRAM_API_KEY. Its MCP server runs with dg mcp; inspect the connected tools because their schemas are supplied by the remote service.
- Your first task
- Transcribe a short authorized recording and compare the returned words, names and numbers with the original audio.
- Billing & payment
- Pay-as-you-go and committed plans charge according to the selected product and model. Speech recognition is priced by audio duration; optional processing features can add charges.
- Agent payment support
- Not verified. Programmatic usage does not establish autonomous checkout support.
- Operational limits
- Language support, concurrency and options vary by model and plan. CLI options do not forward arbitrary API parameters. A completed transcription can still contain errors.
ORIGINAL AI AGENT STORE INTEGRATION PLAYBOOK
Keep the transcript traceable to the original audio
Editorial recommendation · Reviewed 2026-10-16
When to choose this service
Choose Deepgram when a workflow needs hosted speech recognition for audio input. Use a representative sample before committing a large recording archive.
The dependency is trained speech-model inference and its serving capacity. Ordinary transcription orchestration code does not supply the acoustic model or compute service.
Suggested workflow
- Record the input identity, duration, language and required output format. Select the model and estimate the bounded job cost.
- Transcribe a short sample and compare difficult names, numbers and overlapping speech with the audio. Adjust only supported options.
- Process the approved batch while retaining file identifiers and job metadata. Keep uncertain passages marked for review before using the transcript in consequential decisions.
Acceptance checks before real work
- Confirm the transcript covers the expected audio duration.
- Check speaker labels and timestamps where the chosen output provides them.
- Verify critical terms against the audio instead of treating fluent text as proof of accuracy.
If the workflow fails
On partial or failed processing, retain completed outputs and retry only the affected input. For unclear speech, preserve the uncertain passage and seek a better recording or human review.