Gladia (Speech AI) MCP Server for CrewAIGive CrewAI instant access to 6 tools to Delete Transcription, Get Transcription, Init Live Session, and more

Name: Gladia (Speech AI)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Connect your CrewAI agents to Gladia (Speech AI) through Vinkius, pass the Edge URL in the `mcps` parameter and every Gladia (Speech AI) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The Gladia (Speech AI) MCP Server for CrewAI is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Gladia (Speech AI) Specialist",
    goal="Help users interact with Gladia (Speech AI) effectively",
    backstory=(
        "You are an expert at leveraging Gladia (Speech AI) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Gladia (Speech AI) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About 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.

When paired with CrewAI, Gladia (Speech AI) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Gladia (Speech AI) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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.

The Gladia (Speech AI) MCP Server exposes 6 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 Gladia (Speech AI) tools available for CrewAI

When CrewAI connects to Gladia (Speech AI) through Vinkius, your AI agent gets direct access to every tool listed below — spanning speech-to-text, transcription, audio-analysis, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

delete

Delete transcription on Gladia (Speech AI)

Delete a transcription job

get

Get transcription on Gladia (Speech AI)

Get status and results of a transcription job

init

Init live session on Gladia (Speech AI)

Initiate a live transcription session

init

Init transcription on Gladia (Speech AI)

Start a pre-recorded transcription job

list

List transcriptions on Gladia (Speech AI)

List pre-recorded transcriptions

upload

Upload audio file on Gladia (Speech AI)

Upload an audio file to Gladia

Connect Gladia (Speech AI) to CrewAI via MCP

Follow these steps to wire Gladia (Speech AI) into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 6 tools from Gladia (Speech AI)

Why Use CrewAI with the Gladia (Speech AI) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Gladia (Speech AI) through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Gladia (Speech AI) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Gladia (Speech AI) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Gladia (Speech AI) for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Gladia (Speech AI), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Gladia (Speech AI) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Gladia (Speech AI) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Gladia (Speech AI) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Gladia (Speech AI) immediately.

"List my 5 most recent transcription jobs."

"Start a transcription for this audio URL with summarization enabled: https://example.com/audio.mp3"

"I need a WebSocket URL to start a live transcription session in 16000Hz."

Troubleshooting Gladia (Speech AI) MCP Server with CrewAI

Common issues when connecting Gladia (Speech AI) to CrewAI through Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Gladia (Speech AI) + CrewAI FAQ

Common questions about integrating Gladia (Speech AI) MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.