PP

Particle Pro

pro.particle/particle-pro

Podcast intelligence for agents: transcripts, clips, speaker diarization, mention tracking.

Yes, your AI can use this right now.Answered a live MCP handshake in 331 ms with no sign-in needed and exposes 34 tools.
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URL: https://mcp.particle.pro

34 tools, pulled live

Pulled straight from the server with tools/list on 2026-10-27.
particle_alert_createcan modify

Create an alert that watches a single entity and sets up recurring email delivery to external recipients whenever it is mentioned on a podcast episode (kind=ENTITY_MENTION) or appears as a speaker (kind=PODCAST_SPEAKER). Pass the entity slug from a resolve tool — resolve a name with particle_entity_resolve, then create the alert with the slug it returns. An alert watches exactly one entity; to c

particle_alert_deletecan modify

Delete an alert. This is a soft delete: the alert stops producing matches and disappears from particle_alert_list, but its past matches and deliveries are retained for audit. To pause an alert instead of removing it, use particle_alert_update with is_active=false. Only the alert's creator or an organization OWNER or ADMIN can delete it; an API key acts as the user who created the key. Other calle

particle_alert_getread-only

Fetch a single alert's full configuration — title, kind, cadence, watched entities (with names), notification emails, and any active filters (languages, relevance, source_popularity, speaker_roles). The `filters` section is omitted when the alert carries none. By default the response is just the configuration; request include=['matches'] to embed the most recent matches it has caught and include

particle_alert_listread-only

List the alerts in your project, newest first. Each entry carries the alert `id` — feed it into particle_alert_get for full configuration, particle_alert_list_matches for what it has caught, or particle_alert_update / particle_alert_delete to manage it.

particle_alert_list_matchesread-only

List the matches an alert has caught, newest first — the payoff of an alert. Each match names the watched entity and the podcast episode it was detected on (with episode and podcast slugs that feed particle_podcast_get_episode and particle_podcast_resolve). Use view=detailed to include the transcript excerpts around each mention, and after/before to scope to a date range. Backfilled matches (fro

particle_alert_preview

Preview how often an alert would fire BEFORE creating it. Sweeps the past N days (default 7, max 30) for the given entity (or keyword, for kind=KEYWORD_MENTION) and returns the total match count, a per-day breakdown, and a small sample of the most recent matches with episode context. Use this to size an alert (REALTIME vs DAILY vs WEEKLY cadence) or to confirm the entity slug watches the right thi

particle_alert_updatecan modify

Update an existing alert. Only the fields you pass change; the entities and notifications lists, when provided, replace the whole set (pass a single entity slug from the resolve tools, same as particle_alert_create — an alert watches exactly one entity). A KEYWORD_MENTION alert takes a new `keyword` instead of `entities`. Use is_active to pause or resume an alert without deleting it. An alert's

particle_callcan modify

Dispatch any public Particle tool by name. Compatibility fallback for harnesses that block calling tools that weren't advertised on tools/list — every public Particle tool is executable by name, so prefer calling discovered tools directly when your harness allows it. Identical metering and plan gating apply either way. Use particle_catalog to discover tool names and input schemas. A tool particl

particle_catalogread-only

Browse the full Particle tool catalog. Your tools/list shows only the default categories, but EVERY public Particle tool is callable by name regardless of what was advertised — call this tool to discover the rest. Without arguments: the categorical menu (every category with tool names, one-line summaries, and an `↳` line listing each tool's expand options). With `category`: the full input sch

particle_company_getread-only

Return a bundled profile for one company: identifiers (slug, ticker, domain, CIK, QID, linked entity), name, and description. Request optional sections via `include`: 'people' for current leadership and notable people (person slugs feed `particle_person_get`), 'products' for the three-level product hierarchy, 'competitors' for the competitor list, 'external_links' for the company's LinkedIn, soci

particle_company_resolveread-only

Resolve a company by free-text name, ticker, SEC CIK, Wikidata QID, or domain. Returns candidates with the agent-facing identifier (`slug`, falling back to `domain` or `id`) you should pass to `particle_company_get`, `particle_company_get_podcast_ad_presence`, `particle_podcast_find_mentions` (as `company_slug`), or `particle_podcast_list_episodes`. At least one identifier is required. Multiple a

particle_entity_getread-only

One knowledge-graph entity's profile: name, kind, description, and Wikipedia link. Use it to confirm what a slug from `particle_entity_resolve` actually refers to — especially for the long tail that isn't a person or company (places, organizations, events, products, concepts). When the entity is a linked person or company the response carries the person_slug / company_slug — prefer `particle_

particle_entity_resolveread-only

Resolve any named thing — person, company, place, or other entity — by free-text name in one union search. Each candidate carries a `type` and the canonical `slug` for that type: - `person`: the canonical person slug. Feed it into `particle_person_get`, every `person_slug` parameter (`particle_podcast_find_mentions`, `particle_podcast_search_transcripts`, `particle_podcast_list_episodes`), o

particle_expertise_getread-only

Describe one occupation or field of research and, on request, who is booked under it: its parent, children and crosswalk by default; `include: ["top_guests"]` ranks the guests listed under it by podcast appearances in a window (default the last 30 days, at most 90), and `include: ["top_podcasts"]` ranks the shows that booked them. `standing="established"` ranks only credentialed or recognized expe

particle_expertise_resolveread-only

Turn free text into the occupation and field-of-research codes the speaker-expertise filters take. When a question restricts who is speaking by occupation, profession, credentials or industry ("doctors", "medical professionals", "economists", "people in finance", "lawyers"), the filters, not search wording, decide who speaks. `guest_occupation` takes the everyday word itself, so the first search c

particle_person_getread-only

Return a person's profile: name, current role, and bio, keyed by the canonical person slug from `particle_person_resolve`. Request optional sections via `include`: 'external_links' for LinkedIn/Wikipedia/social profiles, 'podcast_appearances' for their most recent podcast appearances (episode and podcast slugs included for follow-up calls), 'companies' for the full role history, 'sports' for an a

particle_person_resolveread-only

Resolve a person by free-text name. Returns ranked candidates with the canonical person `slug` — the stable handle accepted by `particle_person_get`, by every `person_slug` parameter (`particle_podcast_find_mentions`, `particle_podcast_search_transcripts`, `particle_podcast_list_episodes`), and by `particle_podcast_get_guest`'s `guest_slug`. For bulk resolution, pass a comma-separated `query` â

particle_podcast_find_mentionsread-only

Find dialogue lines where a specific person or company is named in podcast transcripts. ## Three response modes **`format="summary"` (default, wide scan).** Returns up to `limit` episodes (reverse-chronological), each with metadata + the first 10 mention-only lines (just the lines naming the entity, no surrounding dialogue). Use this to see *what's been said across episodes* and decide which epi

particle_podcast_get_episoderead-only

Return a bundled overview of one podcast episode: title, podcast, speakers (with entity slugs), top mentioned entities, and segment/clip counts. By default the response is lean — counts plus the top mentioned entities. Request optional sections via `include`: 'segments' for the structural outline with timestamps, 'entities' for the complete entity list, 'clips' for engagement-ranked highlight c

particle_podcast_get_episode_timeseriesread-only

Time-bucketed episode counts — the purpose-built answer to "how often is X discussed over time". Counts episodes matching the same filters as `particle_podcast_list_episodes` (person, company, entity, podcast, keyword, language, duration, transcript availability) per day, week, or month, plus range totals. `keyword_search` additionally counts matching transcript segments per bucket (exact counts

particle_podcast_get_guestread-only

A guest's podcast-appearance profile: lifetime stats (appearances, distinct podcasts, first/last appearance) plus their most frequent podcasts. Guests are people — the same slug works with `particle_person_get` for the biographical profile. Request optional sections via `include`: 'appearances' for the most recent episode appearances (episode and podcast slugs included for follow-up calls), 'po

particle_podcast_get_mention_trendsread-only

How a person's, company's or entity's podcast mentions are moving, for tracking it week over week. Two modes: - `compare` (default): which podcasts mentioned it in a window (default the last 7 days, at most 90) and how each compares with the equal-length window before it: episode and mention line counts in both, the delta, and a label. A show in both windows is `continuing`; one only in the prev

particle_podcast_get_rankingsread-only

Podcast chart rankings from Apple Podcasts and Spotify, in four modes: - `chart` (default): the current chart for a source/country/category slot, or — with `podcast_slug` — every chart slot that podcast currently holds. - `movers`: the biggest rank changes over `window_days` (risers, fallers, entries, exits). Most `change=new` entries are established shows returning to the chart; for new p

particle_podcast_get_share_of_voiceread-only

Split a person's, company's or entity's podcast mentions by who said them: the speakers' occupations (SOC 2018) or fields of research (ANZSRC 2020). Answers "who is talking about NVIDIA — investors, engineers, journalists?" in one call: each group's mention lines, share, distinct speakers and episodes over a window (default the last 30 days, at most 365), optionally bucketed by day, week or mont

particle_podcast_get_transcription_requestread-only

Read where your organization's transcription request stands, by request_id or by the episode's episode_slug. Free: this is how to wait for a transcription that particle_podcast_request_transcription queued, so poll it every minute or so (a transcription usually takes 5 to 10 minutes) rather than requesting again. state is queued (waiting its turn), admitted (being transcribed), transcribed (the e

particle_podcast_list_clipsread-only

Browse AI-extracted highlight clips across the catalog, ranked by engagement potential — the shareable moments. Filter by podcast, episode, clip type (FUNNY, CONTROVERSIAL, INSIGHTFUL, ...), minimum engagement score, or speaker — `speaker` takes a person slug and returns only clips of that person talking ('an insightful Sam Altman clip'). Pass `clip_id` for one clip's full detail (description

particle_podcast_list_episodesread-only

List episodes across the catalog with rich filters: by podcast, person, company, language, date range, duration, or transcript availability. By default it lists the episodes we have ingested. Pass `transcript_status` with `podcast_slug` to reach the show's back catalogue — older episodes discovered in its feed but not transcribed, marked requestable. Their transcript, segments, speakers and ent

particle_podcast_list_guestsread-only

Browse podcast guests across the catalog, in two opinionated modes: - `directory` (default): the guest directory ranked by lifetime appearances (guests with 2+ appearances). - `trends`: who's making the rounds right now — guests with appearances on 2+ distinct podcasts in the last 30 days, which surfaces cross-show press tours rather than show regulars. The press-tour shape is enforced: ever

particle_podcast_list_relatedread-only

List the shows most related to a podcast, best first — "shows like this show". Each result carries the related show's slug, a calibrated score in (0,1], and a coarse band (strong: same beat and audience; moderate: overlapping subject or audience; weak: a loose connection) to branch on. Add `include: ["basis"]` to see WHY each pair is related: content similarity of recent episodes, shared topics,

particle_podcast_list_related_episodesread-only

Episodes from OTHER shows that cover the same story or subject as a given episode, best first — a live nearest-neighbour search over episode content, reranked on shared salient entities, shared topics and a shared news story. Each row carries a calibrated score and a band (strong / moderate / weak) to branch on; pass `include: ["basis"]` to see the signals behind every match. Each show contribut

particle_podcast_request_transcription

Request the transcription of a back-catalogue episode: one discovered in its podcast's feed but not yet transcribed, which particle_podcast_list_episodes (transcript_status=requestable, with podcast_slug) and particle_podcast_get_episode mark requestable. Its transcript, segments, speakers, entities and mentions do not exist until it is transcribed. Billing: the request that queues the episode is

particle_podcast_resolveread-only

Find a podcast by free-text title, exact slug, iTunes ID, or RSS feed URL. Returns slug, title, episode count, bias, and the top recurring speakers (with entity slugs). Use the slug as the agent-facing handle to feed into other podcast tools (`particle_podcast_find_mentions`, `particle_podcast_list_episodes`, `particle_podcast_get_sponsors`). Free-text matching is forgiving — typos, missing or

particle_podcast_search_transcriptsread-only

Search the podcast catalog by what is said in episodes — by meaning (`semantic_search`), by exact phrase (`keyword_search`), or both at once (hybrid ranking). This is THE way to retrieve relevant dialogue, segments, and clips: each result is one segment of one episode with bounded transcript windows pinpointing the highest-relevance lines, plus any highlight clips that overlap the segment inline

particle_topic_browseread-only

Navigate the topic taxonomy. Without `parent_slug`, returns the top-level roots (Politics, Business, Technology, etc.). With `parent_slug` set, returns the direct children of that topic. Topic slugs use a `parent/child` convention (e.g. `politics/elections`) and let agents browse the hierarchy to find well-named categories. To find a topic by name instead of walking the tree, pass `query` (e.g. `

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