Compatible with every major AI agent and IDE
What is the Speechmatics MCP Server?
Connect Speechmatics to your AI agent to handle advanced audio processing workflows. This server enables high-accuracy transcription and natural-sounding speech synthesis through a simple interface.
What you can do
- Batch Transcription — Submit audio via URL or base64 and process large files with industry-leading accuracy using
create_job. - Text-to-Speech (TTS) — Convert text into natural human speech using high-quality voices like Sarah, Theo, Megan, or Jack via
generate_tts. - Transcript Retrieval — Export completed transcriptions in multiple formats including JSON, plain text, or SRT subtitles using
get_transcript. - Job Management — Monitor the status of your processing tasks, list recent activity, and manage resources with
list_jobsandget_job. - Usage & Security — Track your account consumption with
get_usageand generate temporary keys for secure client-side access usingcreate_temp_key.
How it works
- Subscribe to this server
- Enter your Speechmatics API Key
- Start transcribing audio or generating speech directly from Claude, Cursor, or any MCP client
Who is this for?
- Content Creators — Automatically generate subtitles (SRT) for videos or transcribe podcasts in seconds.
- Developers — Integrate speech capabilities into apps without managing complex audio infrastructure.
- Data Analysts — Convert large volumes of recorded meetings or calls into searchable text for analysis.
Built-in capabilities (8)
Create a new batch transcription job
Create a temporary API key
Delete a transcription job
Generate speech from text (TTS)
Get details for a specific job
Retrieve the transcript for a job
Get usage statistics
List recent transcription jobs
Why CrewAI?
When paired with CrewAI, Speechmatics becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Speechmatics tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
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
mcpsparameter 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
Speechmatics in CrewAI
Speechmatics and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Speechmatics to CrewAI 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 Speechmatics in CrewAI
The Speechmatics 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 8 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI 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
Speechmatics for CrewAI
Every tool call from CrewAI to the Speechmatics MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
What formats can I get my transcripts in?
You can use the get_transcript tool to retrieve results in json, txt, or srt (subtitle) formats. Simply specify the format parameter when calling the tool.
Which voices are available for Text-to-Speech?
The generate_tts tool supports four high-quality voices: sarah, theo, megan, and jack. You can choose the one that best fits your content's tone.
How do I check if my transcription job is finished?
Use the get_job tool with your specific job_id. It will return the current status (e.g., running, completed) and metadata about the processing task.
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.
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.
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