Initial skills documentation — 25 categories, all SKILL.md + references + scripts

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# Remote H2 Database Query via SSH
When an MCP server needs to read from an H2 database on a remote host (e.g., Traccar on app2), use this pattern:
## Architecture
```
MCP tool call
→ SSH into remote host (key-based, no password prompt)
→ scp the .mv.db file to a local temp file
→ Java H2 Shell query (org.h2.tools.Shell)
→ Parse pipe-delimited output
→ Delete temp file
→ Return structured JSON
```
## Why this pattern
- **H2 databases lock.** You cannot query a live H2 database from two processes simultaneously. Copying with `scp` creates a read-only snapshot — the copy succeeds even while the DB is in use, and you query the copy.
- **Java is needed.** H2's file format is proprietary. Python libraries like `jaydebeapi` exist but are brittle; the H2 Shell jar is self-contained and reliable.
- **30-second cache.** The SCP + Java query takes 3-5 seconds. Caching avoids this overhead on repeated calls.
## Prerequisites
On the local host:
```bash
apt-get install -y default-jre-headless
# Copy H2 jar from the remote host or the container
scp root@remote:/tmp/h2.jar /tmp/h2.jar
# Test: java -cp /tmp/h2.jar org.h2.tools.Shell --help
```
On the remote host (the H2 jar must exist):
```bash
# If inside a Docker container:
docker cp container_name:/opt/app/lib/h2-*.jar /tmp/h2.jar
```
## Implementation Template
```python
import subprocess, tempfile, os, time
HOST = "152.53.xxx.xxx"
DB_PATH = "/root/docker/app/data/database"
CACHE_TTL = 30
_cache = {"data": None, "ts": 0}
def query_devices():
if _cache["data"] and (time.time() - _cache["ts"]) < CACHE_TTL:
return _cache["data"]
tmp_db = tempfile.mktemp(suffix=".mv.db")
# 1. Copy DB snapshot from remote
subprocess.run(
["scp", "-i", "/root/.ssh/itpp-infra", "-o", "StrictHostKeyChecking=no",
f"root@{HOST}:{DB_PATH}.mv.db", tmp_db],
capture_output=True, timeout=15, check=True
)
# 2. Query with Java H2 Shell
base = tmp_db.replace(".mv.db", "")
result = subprocess.run(
["java", "-cp", "/tmp/h2.jar", "org.h2.tools.Shell",
"-url", f"jdbc:h2:{base}", "-user", "sa", "-password", "",
"-sql", "SELECT id, name, latitude, longitude FROM tc_devices;"],
capture_output=True, text=True, timeout=20
)
os.unlink(tmp_db)
# 3. Parse pipe-delimited output (H2 Shell format)
# Output: "ID | NAME | LATITUDE | LONGITUDE\n1 | foo | 10.4 | -75.5"
rows = []
for line in result.stdout.strip().split('\n'):
parts = [p.strip() for p in line.split('|')]
if len(parts) >= 4 and parts[0].strip().isdigit():
rows.append({
"id": int(parts[0]),
"name": parts[1] if parts[1] != "null" else None,
})
data = {"rows": rows, "count": len(rows)}
_cache["data"] = data
_cache["ts"] = time.time()
return data
```
## Traccar Schema Reference (GPS Tracking)
These are the live table schemas used by Traccar 6.x. All queries go through the H2 database at `/root/docker/traccar/traccar-data/database.mv.db` on app2 (152.53.39.202).
### tc_devices
| Column | Type | Notes |
|---|---|---|
| id | INT | Primary key |
| name | VARCHAR | User-assigned device name |
| uniqueid | VARCHAR | Device identifier (IMEI, serial) |
| lastupdate | TIMESTAMP | Last position received |
| status | VARCHAR | "online", "offline", or "unknown" |
### tc_positions
| Column | Type | Notes |
|---|---|---|
| id | BIGINT | Auto-increment |
| deviceid | INT | FK → tc_devices.id |
| latitude | DOUBLE | Decimal degrees |
| longitude | DOUBLE | Decimal degrees |
| speed | DOUBLE | Knots (× 1.15078 for mph) |
| devicetime | TIMESTAMP | Device-reported time |
### Common Queries
```sql
-- All devices with latest position (one query)
SELECT d.id, d.name, d.uniqueid, d.lastupdate, d.status,
p.latitude, p.longitude, p.speed, p.devicetime
FROM tc_devices d
LEFT JOIN tc_positions p ON p.id = (
SELECT MAX(id) FROM tc_positions WHERE deviceid = d.id
)
ORDER BY d.lastupdate DESC;
-- Position history for one device
SELECT latitude, longitude, speed, devicetime
FROM tc_positions WHERE deviceid = 1
ORDER BY devicetime ASC;
-- Stats: distance (haversine), max speed, active time
SELECT COUNT(*) as positions,
MAX(speed) * 1.15078 as max_speed_mph
FROM tc_positions
WHERE deviceid = 1
AND devicetime >= NOW() - INTERVAL '24' HOUR;
```
## FastAPI Proxy Integration
When the MCP server is slow (3-5s per SCP+Java query), serve data through a FastAPI proxy with 30-second caching. The ops portal at `/opt/ops-portal/server.py` uses this pattern:
```python
# /api/ft360/status endpoint proxies Traccar data
@app.get("/api/ft360/status")
async def traccar_status():
return _get_traccar_data() # cached 30s, SCP+Java underneath
```
The JavaScript dashboard fetches from `/api/ft360/status` every 30 seconds — same TTL as the cache. No authentication needed; the proxy handles the SSH and Java complexity.
- **Java must be on PATH.** Install `default-jre-headless` before using. The `java` binary in Docker containers (e.g., `/opt/traccar/jre/bin/java`) isn't on PATH by default.
- **H2 jar must be on the same host and compatible.** Copy it from the container or remote host — don't download a different version from Maven Central.
- **H2 Shell output format.** The first line is column headers (`ID | NAME | ...`), subsequent lines are data. Filter with `.isdigit()` on the first column.
- **SCP key must work.** The SSH key path must be absolute, and `StrictHostKeyChecking=no` avoids prompt-freezing on first connection.
- **Temp file cleanup.** Always `os.unlink(tmp_db)` in a `finally` block or immediately after the query. A 176KB file won't cause issues if left, but it's sloppy.
- **Cache invalidation.** If you stop+start the remote container (restarting the DB), the cache may return stale data until the TTL expires. For write operations, skip the cache.