Fibery MCP — Installieren & Live-Demo

Warum nutzen

Hauptfunktionen

Auto-discovers your custom Fibery types via the schema API
Read/write entities with rich-text descriptions
Cross-database links (Feature → Customer Insight, etc.)
Fibery formula execution for derived fields
Workspace-scoped token

Live-Demo

In der Praxis

fibery-mcp.replay ▶ bereit

0/0

Installieren

Wählen Sie Ihren Client

~/Library/Application Support/Claude/claude_desktop_config.json · Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "fibery-mcp": {
      "command": "uvx",
      "args": [
        "fibery-mcp-server"
      ]
    }
  }
}

Öffne Claude Desktop → Settings → Developer → Edit Config. Nach dem Speichern neu starten.

~/.cursor/mcp.json · .cursor/mcp.json

{
  "mcpServers": {
    "fibery-mcp": {
      "command": "uvx",
      "args": [
        "fibery-mcp-server"
      ]
    }
  }
}

Cursor nutzt das gleiche mcpServers-Schema wie Claude Desktop. Projektkonfiguration schlägt die globale.

VS Code → Cline → MCP Servers → Edit

{
  "mcpServers": {
    "fibery-mcp": {
      "command": "uvx",
      "args": [
        "fibery-mcp-server"
      ]
    }
  }
}

Klicken Sie auf das MCP-Servers-Symbol in der Cline-Seitenleiste, dann "Edit Configuration".

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "fibery-mcp": {
      "command": "uvx",
      "args": [
        "fibery-mcp-server"
      ]
    }
  }
}

Gleiche Struktur wie Claude Desktop. Windsurf neu starten zum Übernehmen.

~/.continue/config.json

{
  "mcpServers": [
    {
      "name": "fibery-mcp",
      "command": "uvx",
      "args": [
        "fibery-mcp-server"
      ]
    }
  ]
}

Continue nutzt ein Array von Serverobjekten statt einer Map.

~/.config/zed/settings.json

{
  "context_servers": {
    "fibery-mcp": {
      "command": {
        "path": "uvx",
        "args": [
          "fibery-mcp-server"
        ]
      }
    }
  }
}

In context_servers hinzufügen. Zed lädt beim Speichern neu.

claude mcp add fibery-mcp -- uvx fibery-mcp-server

Einzeiler. Prüfen mit claude mcp list. Entfernen mit claude mcp remove.

Anwendungsfälle

Praxisnahe Nutzung: Fibery MCP

Convert customer insights into prioritized feature requests

👤 Product managers using Fibery ⏱ ~15 min intermediate

Wann einsetzen: You have a stack of Insight entities and need to roll them up into Features.

Voraussetzungen

Server/skill installed and authenticated — See repo README

Ablauf

Pull recent insights

Find Insight entities created this month grouped by theme.✓ Kopiert

→ Themed clusters of insights
Create features

For the top 3 themes, create a Feature entity linked to all contributing Insights with a 'why now' summary.✓ Kopiert

→ Three new Features with backlinks

Ergebnis: Backlog grounded in real user feedback with traceability.

Fallstricke

Fibery types are workspace-specific — Fibery types are workspace-specific — always start with describe_schema before assuming a field name.

Kombinieren mit: filesystem

Kombinationen

Mit anderen MCPs für 10-fache Wirkung

fibery-mcp + filesystem

Pair with filesystem for complementary capabilities

Use this server together with filesystem to complete a multi-step task.✓ Kopiert

Werkzeuge

Was dieses MCP bereitstellt

Werkzeug	Eingaben	Wann aufrufen	Kosten
describe_schema	(none)	First — to discover types and fields	1 API call
query_entities	type, filter, limit	Find entities matching criteria	1 API call
update_entity	id, fields	Change a field value	1 API call

Kosten & Limits

Was der Betrieb kostet

API-Kontingent: See provider docs for rate limits
Tokens pro Aufruf: Varies by tool
Kosten in €: See repo README for pricing details
Tipp: Cache tool results and avoid repeated identical calls.

Sicherheit

Rechte, Secrets, Reichweite

Credential-Speicherung: Use environment variables; never commit secrets

Datenabfluss: Tool calls go to the provider's API as documented

Fehlerbehebung

Häufige Fehler und Lösungen

401 Unauthorized

Generate an API token at Fibery workspace settings → API keys. Set FIBERY_HOST and FIBERY_TOKEN.

Prüfen: describe_schema returns types

field not found

Field names in Fibery's API use the type-qualified form (e.g. Workflow/State). Use describe_schema to find the exact name.

Prüfen: Inspect the type's fields

Alternativen

Fibery MCP vs. andere

Alternative	Wann stattdessen	Kompromiss
Linear MCP	Eng-only	Fixed schema; less flexible

Mehr

Ressourcen

📖 Offizielle README auf GitHub lesen

🐙 Offene Issues ansehen

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