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Monitoring earthquake data in Indonesia using BMKG official data. Use when the user asks for the latest earthquake, felt earthquakes, or information about a specific seismic event in Indonesia.
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Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
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| name | bmkg-monitor |
| description | Monitoring earthquake data in Indonesia using BMKG official data. Use when the user asks for the latest earthquake, felt earthquakes, or information about a specific seismic event in Indonesia. |
Monitor and analyze seismic activity in Indonesia using real-time data from the Badan Meteorologi, Klimatologi, dan Geofisika (BMKG).
Run the monitor script to fetch the latest data:
# Get the latest significant earthquake (M5.0+)
python3 scripts/get_gempa.py latest
# Get list of earthquakes felt by people (including smaller ones)
python3 scripts/get_gempa.py felt
# Get recent history of M5.0+ earthquakes
python3 scripts/get_gempa.py recent
# Get detailed Moment Tensor and Phase history
python3 scripts/get_gempa.py detail <EVENT_ID>
If a user reports feeling a tremor or asks "Was there a quake?", run get_gempa.py felt first. This list includes smaller, shallow quakes that people actually feel.
When a significant quake occurs, use references/seismology.md to explain:
If the user provides a "Moment Tensor" or "Beach Ball" diagram (usually from a detailed BMKG report), refer to the "Moment Tensor" section in references/seismology.md to identify if the quake was Strike-Slip, Normal, or Thrust.