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feat: add direct database access for scripts (v0.2.0)

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Implement persistent SQLite database feature that allows scripts to
query schedule data directly via SQL after loading XER files through MCP.

Key changes:
- Extend load_xer with db_path parameter for persistent database
- Add get_database_info tool to retrieve database connection details
- Add schema introspection with tables, columns, primary/foreign keys
- Support WAL mode for concurrent read access
- Use atomic write pattern to prevent corruption

New features:
- db_path=None: in-memory database (default, backward compatible)
- db_path="": auto-generate path from XER filename (.sqlite extension)
- db_path="/path/to/db": explicit persistent database path

Response includes complete DatabaseInfo:
- db_path: absolute path (or :memory:)
- is_persistent: boolean
- source_file: loaded XER path
- loaded_at: ISO timestamp
- schema: tables with columns, primary keys, foreign keys, row counts

Closes: User Story 1, 2, 3 from 002-direct-db-access spec
This commit is contained in:
Bill Ballou
2026-01-08 12:54:56 -05:00
parent 3e7ad39eb8
commit d6a79bf24a
11 changed files with 1064 additions and 40 deletions
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58
src/xer_mcp/db/queries.py
View File

@@ -239,16 +239,18 @@ def query_relationships(
lag_hours=row[6] or 0.0,
pred_type=pred_type,
)
relationships.append({
"task_pred_id": row[0],
"task_id": row[1],
"task_name": row[2],
"pred_task_id": row[3],
"pred_task_name": row[4],
"pred_type": pred_type,
"lag_hr_cnt": row[6],
"driving": driving,
})
relationships.append(
{
"task_pred_id": row[0],
"task_id": row[1],
"task_name": row[2],
"pred_task_id": row[3],
"pred_task_name": row[4],
"pred_type": pred_type,
"lag_hr_cnt": row[6],
"driving": driving,
}
)
return relationships, total
@@ -298,14 +300,16 @@ def get_predecessors(activity_id: str) -> list[dict]:
lag_hours=row[4] or 0.0,
pred_type=pred_type,
)
result.append({
"task_id": row[0],
"task_code": row[1],
"task_name": row[2],
"relationship_type": pred_type,
"lag_hr_cnt": row[4],
"driving": driving,
})
result.append(
{
"task_id": row[0],
"task_code": row[1],
"task_name": row[2],
"relationship_type": pred_type,
"lag_hr_cnt": row[4],
"driving": driving,
}
)
return result
@@ -355,14 +359,16 @@ def get_successors(activity_id: str) -> list[dict]:
lag_hours=row[4] or 0.0,
pred_type=pred_type,
)
result.append({
"task_id": row[0],
"task_code": row[1],
"task_name": row[2],
"relationship_type": pred_type,
"lag_hr_cnt": row[4],
"driving": driving,
})
result.append(
{
"task_id": row[0],
"task_code": row[1],
"task_name": row[2],
"relationship_type": pred_type,
"lag_hr_cnt": row[4],
"driving": driving,
}
)
return result