Signalcrest

Cross-source trend signals from 10 developer communities, scored every 30 minutes.

Sollte ich dies verwenden

Qualität und Sicherheit

A
Qualität der Beschreibung
100%
Vollständigkeit des Schemas
95%
Qualität der Benennung
100%
Risiko der Vergiftung
80%
Übereinstimmung der Berechtigungen
100%
Einhaltung des Protokolls
100%

Befunde (2)

  • HIGHTool poisoning patterns detected
  • INFOTool description contains placeholder or incomplete textin list_signals

Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.

Kontextkosten

~617Tokens (Tool-Definitionen)
~855 BTypische Antwortgröße
Minimale Auswirkung auf die Aufmerksamkeit (0.48% von 128k Kontext)

Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.

Installieren

Installation mit einem Klick

Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:

{
  "mcpServers": {
    "signalcrest": {
      "url": "https://www.signalcrest.app/api/mcp"
    }
  }
}

Remote-Endpunkte

https://www.signalcrest.app/api/mcpstreamable-http

Was es kann

Tool-Inventar

Tools (4)

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🟢list_signals(category, limit)

Top technology signals ranked by momentum right now, scored every 30 minutes across ten developer and builder communities (Hacker News, GitHub, Stack Overflow, npm, Hugging Face, Dev.to, Lobsters, Product Hunt, arXiv, crypto governance forums). Call this to find what is gaining traction before it reaches search-trend tools — e.g. when the user asks what is emerging, trending, or worth paying attention to in a technology area. Returns live unredacted data with no delay.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "enum": [
        "ai",
        "devtools",
        "security",
        "web",
        "data",
        "crypto",
        "hardware",
        "business",
        "science",
        "other"
      ],
      "description": "Restrict to one category. Omit for all categories."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 200,
      "description": "How many signals to return (default 50, max 200)."
    }
  },
  "required": [],
  "additionalProperties": false
}
🟢get_topic(id)

Full detail and complete score history for one topic, by id (e.g. "hn:48910545", "gh:1287845516"). Call this after list_signals to see how a specific signal has moved over time, its cross-source corroboration, and its lifecycle stage. Ids come from list_signals.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Topic id as returned by list_signals, e.g. \"hn:48910545\"."
    }
  },
  "required": [
    "id"
  ],
  "additionalProperties": false
}
🟢list_entities(category, limit)

Trending entities (products, companies, libraries, technologies) ranked by cross-source momentum. An entity aggregates every post, repo and release mentioning it across ten developer and builder communities — one row per trend rather than per post. Prefer this over list_signals when the user asks about trends or technologies; use list_signals for individual posts.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "enum": [
        "ai",
        "devtools",
        "security",
        "web",
        "data",
        "crypto",
        "hardware",
        "business",
        "science",
        "other"
      ],
      "description": "Restrict to one category. Omit for all categories."
    },
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 200,
      "description": "How many entities to return (default 50, max 200)."
    }
  },
  "required": [],
  "additionalProperties": false
}
🟢get_entity(name)

Full detail for one entity by name (e.g. "kubernetes"): current composite score, complete score history, which communities are talking about it, and the live member items (evidence) behind the score. Names come from list_entities.

Eingabe-Schema

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Entity name as returned by list_entities, e.g. \"kubernetes\"."
    }
  },
  "required": [
    "name"
  ],
  "additionalProperties": false
}

Community

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