Particle launches Radar to index 130000 podcasts for AI agents via API and MCP
Particle has launched Radar, a podcast intelligence platform that transcribes and analyzes more than 130,000 podcasts, turning long-form audio into searchable, machine-queryable data. According to TechCrunch, Radar exposes that corpus through a web interface, a programmatic API, and MCP integration so AI agents and businesses can retrieve podcast conversations without manual listening. The move positions Particle as infrastructure for agentic workflows that need timely context from spoken media, not just web pages or documents. Operators building retrieval-augmented systems may gain a new vertical data source, though the packet does not specify pricing, transcription accuracy, update latency, licensing limits, or which podcasts are included beyond the indexed count.
Particle launches Radar to index 130000 podcasts for AI agents via API and MCP
Particle introduced Radar, a podcast search engine that transcribes and analyzes more than 130,000 podcasts. The platform exposes podcast intelligence through a web interface, an API, and MCP so AI agents and businesses can query transcribed audio programmatically.
Key takeaway
Radar gives AI agents programmatic access to transcribed podcast intelligence across 130,000+ shows via API and MCP.
What happened
According to TechCrunch AI, Particle introduced Radar, a podcast search engine that transcribes and analyzes more than 130,000 podcasts for programmatic access.
The platform exposes podcast intelligence through a web interface, an API, and MCP so AI agents and businesses can query transcribed audio without manual listening.
Evidence
Particle introduced Radar to transcribe and analyze more than 130,000 podcasts.
TechCrunch AI · attributed
Particle introduced Radar, a podcast search engine that transcribes and analyzes more than 130,000 podcasts.
Radar exposes podcast intelligence through a web interface, an API, and MCP.
TechCrunch AI · attributed
The platform exposes podcast intelligence through a web interface, an API, and MCP so AI agents and businesses can query transcribed audio programmatically.
Radar makes podcast conversations searchable on the web and accessible to AI agents.
TechCrunch AI · attributed
Particle's new podcast intelligence platform transcribes and analyzes more than 130,000 podcasts, making their conversations searchable on the web and accessible to AI agents through an API and MCP.
Why it matters
Spoken-media archives are hard for agents to use at scale; a indexed transcript layer with API and MCP access could expand retrieval beyond text-native corpora.
Limits and uncertainties
The evidence packet does not report pricing, transcription accuracy, indexing refresh rates, or licensing terms for Radar.
Coverage is described only as more than 130,000 podcasts, without a public list of included shows or publishers.
Practical implications
Agent builders can evaluate Radar's API and MCP endpoints as a podcast retrieval layer for RAG and research workflows.
Teams should map Radar's transcript corpus against their compliance and attribution requirements before production use.
What to watch
Whether Particle publishes pricing, rate limits, and MCP tool schemas for Radar integrations.
How quickly new episodes from major podcasts appear in the indexed corpus after release.
