Audioscrape Audio Intelligence

What Audioscrape Audio Intelligence MCP server does

The Audioscrape Audio Intelligence MCP server is intended for searching spoken content across several audio source types. The provided description names podcasts, government meetings, and audio supplied by the user as supported search targets. This makes the server relevant to workflows that need to find speech rather than handle audio as an undifferentiated file.

Search results include contextual information about the matching speech. The listed result dimensions are speakers, entities, and timestamps. Speaker information can help identify who is associated with a passage, entity information can indicate which named subjects appear in the result, and timestamps can locate the passage within the source audio. The available material does not describe the exact response format or whether every result includes all three fields.

Tools and capabilities

The Audioscrape Audio Intelligence MCP server is described as providing speech search. Its stated coverage includes:

• Searching speech in podcasts.
• Searching speech in government meetings.
• Searching speech in the user’s own audio.
• Returning or identifying speaker, entity, and timestamp context for speech matches.

These capabilities support audio-oriented question answering and discovery tasks where an agent must locate relevant spoken material. The supplied description does not name individual MCP tool identifiers, parameters, pagination behavior, indexing controls, upload methods, or filtering syntax. Treat those details as unspecified until the service documentation provides them.

Limitations and notes

The available source is the Audioscrape website URL and a short product description; a README was not provided. As a result, setup instructions, authentication requirements, transport options, environment variables, licensing, supported MCP clients, and operational limits cannot be confirmed here. The material also does not state which audio formats are accepted, how a user’s own audio is added, whether audio is transcribed before search, or how speakers and entities are identified.

The Audioscrape Audio Intelligence MCP server should therefore be evaluated primarily against its documented core use case: searching speech across podcasts, government meetings, and personal audio with speaker, entity, and timestamp context. Confirm installation and integration requirements from the service’s current documentation before configuring it in an agent environment.