Bring Speech To Text
to LlamaIndex
Learn how to connect Gladia (Speech AI) to LlamaIndex 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 LlamaIndex?
LlamaIndex agents combine Gladia (Speech AI) tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine Gladia (Speech AI) tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Gladia (Speech AI) tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Gladia (Speech AI), a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Gladia (Speech AI) tools were called, what data was returned, and how it influenced the final answer
Gladia (Speech AI) in LlamaIndex
Gladia (Speech AI) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Gladia (Speech AI) to LlamaIndex 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 LlamaIndex
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 LlamaIndex 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 LlamaIndex
Every tool call from LlamaIndex 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 LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Gladia (Speech AI) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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