Lightning FM :: MCP Server
Un servidor MCP para el catálogo musical de Lightning FM: busca pistas, consulta artistas y comprueba qué está sonando en la emisora, todo desde un agente.
No existe una API de agente separada. Este servidor lee exactamente lo que lee un cliente humano: eventos de pista kind 31337 y perfiles kind 0 de relays públicos de Nostr, audio e imágenes del servidor público de Blossom, y el evento de actividad en vivo kind 30311 que la emisora publica en cada cambio de pista. Cada pista está firmada con la propia clave del artista: este es el catálogo canónico, no un subconjunto seleccionado que la plataforma mantenga para agentes.
Añádelo a la configuración de servidores de tu cliente MCP. Para Claude Code o Claude Desktop:
{
"mcpServers": {
"lightning-fm": {
"command": "npx",
"args": ["-y", "lightning-fm-mcp"]
}
}
}Sin instalación, sin clave de API, sin cuenta. Habla con relay.lightning.fm y media.lightning.fm por defecto: consulta Configuración para apuntarlo a otro sitio.
Related MCP server: Maximum Sats MCP
search_catalog — búsqueda de texto libre más filtros por género/etiqueta en todo el catálogo. Deja todos los filtros vacíos para explorar de más reciente a más antiguo.
get_artist — busca un artista por nombre visible (coincidencia parcial), clave pública hexadecimal o npub. Devuelve su perfil y discografía completa.
get_now_playing — qué está sonando actualmente en antena y la URL del stream.
Todas las variables de entorno son opcionales: los valores por defecto apuntan a producción. Nada de esto es un secreto; este servidor es de solo lectura y nunca firma ni publica nada.
Variable | Valor por defecto | Qué hace |
|
| URLs de relays separadas por comas para consultar. Añade aquí un relay solo si controla las escrituras como hace relay.lightning.fm: el kind 31337 no es exclusivo de Lightning FM, y un relay público sin restricciones devuelve también las pistas de cualquier otra aplicación. |
|
| Servidor Blossom contra el que se resuelven los hashes de audio/imagen. |
|
| Cuánto tiempo se reutiliza una instantánea obtenida antes de que la siguiente llamada a una herramienta vuelva a consultar los relays. |
npm install
npm run dev # runs src/index.ts directly via tsx
npm run build # tsc -> dist/src/nostr/track.ts replica el parseo del kind 31337 en station-server/src/catalog/track.ts y app-desktop/src-tauri/src/relay.rs. Los tres deben coincidir en los nombres de las etiquetas: este es el formato público de intercambio de la plataforma, documentado por completo en lightning.fm/interop.
MIT
Look up an artist by display name or Nostr pubkey (hex or npub) and return their profile plus every track they have published to Lightning FM.
| Name | Required | Description | Default |
|---|---|---|---|
| artist | Yes | Artist display name (partial match ok), hex pubkey, or npub. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description takes on the full burden. It discloses accepted input formats (display name, hex, npub) and return contents (profile + every published track). It does not describe error handling or what happens on ambiguous matches, and the read-only nature is implied rather than explicit, so a 5 is not warranted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, efficiently worded sentence that front-loads the action and target, then conveys return value without filler. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup with no output schema, the description adequately covers what will be returned (profile + tracks). It leaves a few edge cases unaddressed (e.g., ambiguous names, empty results), but the tool is simple enough that these are minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the schema already explains the parameter well (partial match ok, formats). The description essentially repeats that information without adding extra semantic context about the parameter, so it meets the baseline but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Look up'), the resource ('artist'), and the accepted identifiers (display name or Nostr pubkey), and further specifies that it returns the profile plus all published tracks. However, it does not explicitly differentiate from sibling tools like search_catalog, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is clear: when you need an artist's profile and tracks by name or pubkey, this is the tool. It does not explicitly address when not to use it or mention alternatives, leaving sibling differentiation to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read the current live activity (NIP-53, kind 30311) Lightning FM publishes on every track change: the track currently on air, the stream URL, and station status.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clearly labels the operation as a read, exposes the live/NIP-53 protocol detail, and states what information is returned. It does not mention failure modes, latency, or auth, but for a zero-parameter public read that is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single tight sentence that front-loads the verb and resource, then adds protocol and return details. Every clause earns its place with no repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read with no output schema, the description needs to explain what the tool returns and does, and it does so concretely (track, stream URL, station status). It could slightly improve by noting what happens when no track is currently on air, but the station status detail partially covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so the schema holds no parameter information for the description to enhance. According to the baseline for zero-parameter tools, this is a Strong case: nothing is missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Read'), a specific resource ('current live activity ... Lightning FM publishes'), and the exact data elements returned (track, stream URL, station status). It clearly distinguishes this from sibling search-oriented tools like search_catalog and get_artist by focusing on live, current state rather than catalog lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says it reads current live activity and the track currently on air, which gives clear context for when to use it. It does not explicitly name sibling alternatives or say when not to use it, but the 'current' vs. search distinction is strong enough that an agent should route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search or browse Lightning FM's Nostr-native music catalog (kind 31337 track events, fetched live from wss://relay.lightning.fm). Every result is signed by the artist's own Nostr key — this is the canonical catalog, not a curated subset. Leave all filters empty to browse the whole catalog, newest first.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Match a single free-form keyword tag. | |
| genre | No | Exact or partial genre match, case-insensitive. | |
| limit | No | Max tracks to return (default 20, max 100). | |
| query | No | Free-text match against title, artist name, album, genre, and description. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the live-fetching behavior, the Nostr signature guarantee, the canonical nature of the data, and the default ordering. It does not mention potential latency, relay availability, or result shape, but for a search tool the disclosed traits are substantive and useful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no filler. It front-loads the core purpose, then efficiently adds key contextual facts (live source, signed results, canonical scope, browse behavior). Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search/browse tool with no output schema and no annotations, the description covers purpose, usage, data source, trust properties, and default ordering. It is missing explicit return-format details and error behavior, but the schema covers parameters and the description gives enough context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all parameters are already documented in the schema. The description adds one meaningful behavioral hint—that leaving all filters empty browses the whole catalog—but does not add meaning for individual parameters beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Search or browse') and resource ('Lightning FM's Nostr-native music catalog'), and further distinguishes it by specifying the event kind (31337) and the live relay source. This makes it clearly distinct from the sibling tools get_artist and get_now_playing, which focus on singular or current-state data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives clear usage context: filters can be left empty to browse the entire catalog newest first, and the catalog is live and canonical rather than curated. However, it does not explicitly state when to prefer this tool over the sibling tools or provide exclusion criteria, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.5get_artistget_now_playingsearch_catalogScored across 3 tools
Each tool has a distinct purpose: searching the catalog, looking up an artist, and reading live now-playing data. There is no practical overlap in what an agent would select them for.
All three tools follow a clear verb_noun convention: search_catalog, get_artist, get_now_playing. The naming pattern is predictable and consistent.
Three tools is a tight, well-scoped set for a read-only music catalog API. Each tool covers a distinct high-level user need without unnecessary bloat.
The core domain is covered: catalog browsing/search, artist lookup with tracks, and live playback status. A direct track-by-ID detail lookup is a minor gap, but the other tools can work around it through search or artist queries.
Find Bizzy radio stations, read station cards and public author information. Read-only; no playback.
Generate full songs with vocals, instrumentals and sound effects from text. One server for Suno, Google Lyria, Mureka, MiniMax, ACE-Step, YuE and ElevenLabs. Your agent can quote the credit cost before generating, start a song, wait for it to finish and return download links. Sign in with OAuth; optional daily credit caps; retries never charge twice.
Search, analyze, and discover commercially released music using sonic intelligence.
Neutral commerce resolution for AI agents — music live, ranked by trust, never by commission.
