Skip to main content
Glama
speechweave

@speechweave/mcp

Official
by speechweave

Transcribe local file (wait)

transcribe_file

Transcribe local audio or video files by uploading their absolute file path. Returns the transcript immediately or a job ID for longer recordings.

Instructions

Upload a local audio/video file and wait until transcription finishes. Prefer for short/medium clips when you need the transcript in this turn. Pass an absolute filesystem path (never raw binary). On wait timeout, returns job_id — then call get_job_status. For long audio you plan to poll yourself, use start_job_file instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute local filesystem path to an audio or video file. Relative paths are rejected. Do not pass raw binary over MCP.
modelNoTranscription model tier. core = default balance of speed/accuracy; max = hardest audio.core
languageNoOptional two-letter ISO language code (e.g. en, es).
timeout_msNoMax milliseconds to wait for completion (default 1 hour). On timeout, returns job_id so you can call get_job_status.
service_modeNodeferred = background queue (default, better for long audio); synchronous = higher-priority path with a smaller size cap.deferred
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses wait behavior, timeout handling, and path requirement. Could mention response format on success or file size limits, but core behavior is well covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three focused sentences: action, usage advice, edge case+alternative. No wasted words, front-loaded with key info.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, usage, timeout, and alternative. Lacks explicit mention of normal success return (i.e., transcript text) but handles the main behavioral gap (timeout). Satisfactory given schema richness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for all 5 parameters. The description reinforces the path constraint but adds little beyond schema. Baseline 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Upload a local audio/video file and wait until transcription finishes') and distinguishes it from siblings like 'transcribe_url' (remote URL) and 'start_job_file' (no wait).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises when to use ('Prefer for short/medium clips when you need the transcript in this turn') and when not to, with a direct alternative ('For long audio you plan to poll yourself, use start_job_file instead'). Also explains timeout fallback.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/speechweave/speechweave-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server