Connect Particle Pro and your agent gets 28 tools, among them particle_alert_create, particle_alert_delete, particle_alert_get. It answers at https://mcp.particle.pro over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 12 September 2026; the last check, on 24 October 2026, succeeded.
Podcast intelligence for agents: transcripts, clips, speaker diarization, mention tracking.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
particle_alert_create | Create an alert that watches a single entity and emails you 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 p Inputs: delivery_cadence, description, entities, filters, is_active, kind |
particle_alert_delete | 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_upda Inputs: alert_id |
particle_alert_get | 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 Inputs: alert_id, include, match_limit, output_format |
particle_alert_list | 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 Inputs: cursor, limit, output_format |
particle_alert_list_matches | 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_ Inputs: after, alert_id, before, cursor, limit, output_format |
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 and returns the total match count, a per-day breakdown, and a small sample of the most recent matches with episode con Inputs: entities, filters, kind, output_format, window_days |
particle_alert_update | 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 exactl Inputs: alert_id, delivery_cadence, description, entities, filters, is_active |
particle_call | 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 w Inputs: arguments, tool |
particle_catalog | 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 cat Inputs: category, output_format |
particle_company_get | 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 `pa Inputs: company_slug, include, product_status |
particle_company_resolve | 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_p Inputs: cik, domain, limit, qid, query, ticker |
particle_entity_get | 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, organi Inputs: entity_slug, output_format |
particle_entity_resolve | 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 Inputs: limit, query |
particle_person_get | 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_appearance Inputs: include, output_format, person_slug |
particle_person_resolve | 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_sear Inputs: limit, output_format, query |
particle_podcast_find_mentions | Find dialogue lines where a specific person or company is named in podcast transcripts. ## Two response modes **`format="summary"` (default, wide scan).** Returns up to `limit` episodes (reverse-chronological), each with metadata + the firs Inputs: company_slug, context_lines, cursor, entity_slug, episode_slug, format |
particle_podcast_get_episode | 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 sect Inputs: episode_slug, include, transcript_end, transcript_format, transcript_speaker, transcript_start |
particle_podcast_get_episode_timeseries | 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, t Inputs: company_slug, entity_slug, has_transcript, interval, keyword_search, language |
particle_podcast_get_guest | 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. Inputs: guest_slug, include, output_format |
particle_podcast_get_rankings | 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 bigg Inputs: category_slug, change, country, cursor, limit, mode |
particle_podcast_list_clips | 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` Inputs: clip_id, cursor, episode_slug, include, limit, min_engagement |
particle_podcast_list_episodes | List episodes across the catalog with rich filters: by podcast, person, company, language, date range, duration, or transcript availability. Use this for episode-level discovery when you only need metadata (title, duration, speakers, counts Inputs: company_slug, cursor, entity_slug, has_transcript, language, limit |
particle_podcast_list_guests | 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 appear Inputs: cursor, limit, mode, output_format, podcast_slug, topic_slug |
particle_podcast_list_related | 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 aud Inputs: cursor, exclude_same_publisher, include, language, limit, min_popularity |
particle_podcast_list_related_episodes | 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 carri Inputs: cursor, episode_slug, include, limit, output_format, published_within_days |
particle_podcast_resolve | 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 tool Inputs: include, itunes_id, limit, min_popularity, query, recent_episodes |
particle_podcast_search_transcripts | 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 i Inputs: company_slug, context, cursor, entity_slug, entity_type, episode_slug |
particle_topic_browse | 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. `po Inputs: cursor, limit, output_format, parent_slug |
Every block below points at https://mcp.particle.pro. Pick your client and copy.
claude mcp add --transport http particle-pro https://mcp.particle.pro
{
"mcpServers": {
"particle-pro": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.particle.pro"]
}
}
}{
"mcpServers": {
"particle-pro": {
"url": "https://mcp.particle.pro"
}
}
}{
"servers": {
"particle-pro": {
"type": "http",
"url": "https://mcp.particle.pro"
}
}
}{
"context_servers": {
"particle-pro": {
"url": "https://mcp.particle.pro"
}
}
}{
"mcpServers": {
"particle-pro": {
"serverUrl": "https://mcp.particle.pro"
}
}
}{
"mcpServers": {
"particle-pro": {
"url": "https://mcp.particle.pro"
}
}
}name: Particle Pro
version: 0.0.1
schema: v1
mcpServers:
- name: Particle Pro
type: streamable-http
url: https://mcp.particle.pro{
"mcpServers": {
"particle-pro": {
"httpUrl": "https://mcp.particle.pro"
}
}
}{
"mcpServers": {
"particle-pro": {
"type": "http",
"url": "https://mcp.particle.pro"
}
}
}{
"mcpServers": {
"particle-pro": {
"url": "https://mcp.particle.pro"
}
}
}goose://extension?url=https%3A%2F%2Fmcp.particle.pro&type=streamable_http&id=particle-pro&name=Particle%20Pro
It answered our last check on 24 October 2026 in 232 ms. Over 6 checks since 12 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.
Yes. It is published by particle.pro and served from mcp.particle.pro, the vendor's own domain: https://mcp.particle.pro.
28, as returned by the server's own tools/list on 23 September 2026: particle_alert_create, particle_alert_delete, particle_alert_get, particle_alert_list, particle_alert_list_matches, particle_alert_preview, particle_alert_update, particle_call, and 20 more.
It answered our last check on 24 October 2026 in 232 ms. Over 6 checks since 12 September 2026 it answered 6.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://mcp.particle.pro. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: pro.particle. Endpoint host: mcp.particle.pro. ARD identifier: urn:air:pro.particle:mcp:particle-pro.
First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.