Bring Speech To Text
to Mastra AI
Learn how to connect Gladia (Speech AI) to Mastra AI and start using 6 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Gladia (Speech AI) MCP Server?
Connect Gladia to your AI agent to unlock enterprise-grade speech-to-text capabilities. Process audio files or live streams with advanced features like speaker diarization, multi-language translation, and automated summarization.
What you can do
- Audio Processing — Upload local files to generate secure URLs for immediate transcription processing.
- Advanced Transcription — Initiate jobs with speaker diarization (who said what), summarization, and translation across 100+ languages.
- Audio-to-LLM — Apply custom LLM prompts directly to your audio data to extract specific insights or structured data.
- Live Streaming — Initialize secure WebSocket sessions for real-time transcription of meetings or broadcasts.
- Job Management — List, retrieve, and manage your transcription history and results directly through conversation.
How it works
- Subscribe to this server
- Enter your Gladia API Key
- Start transcribing audio files or live streams from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Developers — Integrate speech-to-text workflows into apps without managing complex API calls manually.
- Content Creators — Quickly generate transcripts, summaries, and translations for podcasts or videos.
- Business Teams — Analyze meeting recordings to extract action items and speaker insights using natural language.
Built-in capabilities (6)
Delete a transcription job
Get status and results of a transcription job
Initiate a live transcription session
Start a pre-recorded transcription job
List pre-recorded transcriptions
Upload an audio file to Gladia
Why Mastra AI?
Mastra's agent abstraction provides a clean separation between LLM logic and Gladia (Speech AI) tool infrastructure. Connect 6 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Gladia (Speech AI) without touching business code
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Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
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TypeScript-native: full type inference for every Gladia (Speech AI) tool response with IDE autocomplete and compile-time checks
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One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Gladia (Speech AI) in Mastra AI
Gladia (Speech AI) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Gladia (Speech AI) to Mastra AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Gladia (Speech AI) in Mastra AI
The Gladia (Speech AI) MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 6 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Mastra AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Gladia (Speech AI) for Mastra AI
Every tool call from Mastra AI to the Gladia (Speech AI) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I check the status of a transcription job I just started?
Use the get_transcription tool with the Job ID. It will return the current status (queued, processing, done, or error) and the results if completed.
Can I automatically identify different speakers in a recording?
Yes! When using init_transcription, set the diarization parameter to true. The AI will then distinguish between different voices in the transcript.
How do I handle a local audio file that isn't online yet?
First, use the upload_audio_file tool by providing the base64 data and filename. This will give you an audio_url that you can then pass to init_transcription.
How does Mastra AI connect to MCP servers?
Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
Can Mastra agents use tools from multiple servers?
Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
Does Mastra support workflow orchestration?
Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.
createMCPClient not exported
Install: npm install @mastra/mcp
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