feat: prepare mi-fitness-mcp for first public release

Package the standalone Mi Fitness MCP with clearer public docs, release metadata, CI, and safer local repository hygiene so it is ready to publish without secrets or work identity leakage.

src/mi_fitness_mcp/server.py

@@ -33,14 +33,113 @@ query_service = None
 @app.list_tools()
 async def list_tools() -> list[Tool]:
     return [
-        Tool(name="get_connection_status", description="Check connection status", inputSchema={"type": "object", "properties": {}}),
-        Tool(name="sync_data", description="Synchronize Mi Fitness data", inputSchema={"type": "object", "properties": {"data_types": {"type": "array", "items": {"type": "string"}}, "start_date": {"type": "string"}, "end_date": {"type": "string"}, "force_full_sync": {"type": "boolean"}}}),
-        Tool(name="get_profile", description="Get user profile information", inputSchema={"type": "object", "properties": {}}),
-        Tool(name="get_daily_summary", description="Get daily activity summary", inputSchema={"type": "object", "properties": {"date": {"type": "string"}, "start_date": {"type": "string"}, "end_date": {"type": "string"}}}),
-        Tool(name="query_metric_series", description="Query metric series", inputSchema={"type": "object", "properties": {"metric": {"type": "string", "enum": ["steps", "distance_m", "active_kcal", "weight_kg"]}, "start_date": {"type": "string"}, "end_date": {"type": "string"}, "granularity": {"type": "string", "enum": ["day", "week", "month"]}, "aggregation": {"type": "string", "enum": ["sum", "avg", "min", "max", "latest"]}}, "required": ["metric", "start_date", "end_date"]}),
-        Tool(name="query_heart_rate", description="Query heart rate samples", inputSchema={"type": "object", "properties": {"start_date": {"type": "string"}, "end_date": {"type": "string"}, "sample_type": {"type": "string", "enum": ["resting", "active", "passive", "workout"]}, "limit": {"type": "integer"}}, "required": ["start_date", "end_date"]}),
-        Tool(name="query_body_measurements", description="Query body measurements", inputSchema={"type": "object", "properties": {"start_date": {"type": "string"}, "end_date": {"type": "string"}, "metrics": {"type": "array", "items": {"type": "string", "enum": ["weight_kg", "bmi", "body_fat_pct", "muscle_mass_kg", "water_pct"]}}, "latest_only": {"type": "boolean"}}, "required": ["start_date", "end_date"]}),
-        Tool(name="get_data_coverage", description="Get data coverage", inputSchema={"type": "object", "properties": {"data_types": {"type": "array", "items": {"type": "string"}}}}),
+        Tool(
+            name="get_connection_status",
+            description="Check connection status",
+            inputSchema={"type": "object", "properties": {}},
+        ),
+        Tool(
+            name="sync_data",
+            description="Synchronize Mi Fitness data",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "data_types": {"type": "array", "items": {"type": "string"}},
+                    "start_date": {"type": "string"},
+                    "end_date": {"type": "string"},
+                    "force_full_sync": {"type": "boolean"},
+                },
+            },
+        ),
+        Tool(
+            name="get_profile",
+            description="Get user profile information",
+            inputSchema={"type": "object", "properties": {}},
+        ),
+        Tool(
+            name="get_daily_summary",
+            description="Get daily activity summary",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "date": {"type": "string"},
+                    "start_date": {"type": "string"},
+                    "end_date": {"type": "string"},
+                },
+            },
+        ),
+        Tool(
+            name="query_metric_series",
+            description="Query metric series",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "metric": {
+                        "type": "string",
+                        "enum": ["steps", "distance_m", "active_kcal", "weight_kg"],
+                    },
+                    "start_date": {"type": "string"},
+                    "end_date": {"type": "string"},
+                    "granularity": {"type": "string", "enum": ["day", "week", "month"]},
+                    "aggregation": {
+                        "type": "string",
+                        "enum": ["sum", "avg", "min", "max", "latest"],
+                    },
+                },
+                "required": ["metric", "start_date", "end_date"],
+            },
+        ),
+        Tool(
+            name="query_heart_rate",
+            description="Query heart rate samples",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "start_date": {"type": "string"},
+                    "end_date": {"type": "string"},
+                    "sample_type": {
+                        "type": "string",
+                        "enum": ["resting", "active", "passive", "workout"],
+                    },
+                    "limit": {"type": "integer"},
+                },
+                "required": ["start_date", "end_date"],
+            },
+        ),
+        Tool(
+            name="query_body_measurements",
+            description="Query body measurements",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "start_date": {"type": "string"},
+                    "end_date": {"type": "string"},
+                    "metrics": {
+                        "type": "array",
+                        "items": {
+                            "type": "string",
+                            "enum": [
+                                "weight_kg",
+                                "bmi",
+                                "body_fat_pct",
+                                "muscle_mass_kg",
+                                "water_pct",
+                            ],
+                        },
+                    },
+                    "latest_only": {"type": "boolean"},
+                },
+                "required": ["start_date", "end_date"],
+            },
+        ),
+        Tool(
+            name="get_data_coverage",
+            description="Get data coverage",
+            inputSchema={
+                "type": "object",
+                "properties": {"data_types": {"type": "array", "items": {"type": "string"}}},
+            },
+        ),
     ]
 
 
@@ -74,7 +173,9 @@ async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
 async def _handle_get_connection_status() -> dict:
     global adapter, config
     if not config or config.mode == "not_configured":
-        return ConnectionStatus(mode="not_configured", connected=False, message="Server not configured.").model_dump()
+        return ConnectionStatus(
+            mode="not_configured", connected=False, message="Server not configured."
+        ).model_dump()
 
     connected = adapter is not None and adapter.is_connected()
     last_sync = None
@@ -87,7 +188,12 @@ async def _handle_get_connection_status() -> dict:
                 sync_time = datetime.fromisoformat(state["last_sync_at"])
                 if last_sync is None or sync_time > last_sync:
                     last_sync = sync_time
-    return ConnectionStatus(mode=config.mode, connected=connected, last_sync_at=last_sync, available_data_types=available_types).model_dump()
+    return ConnectionStatus(
+        mode=config.mode,
+        connected=connected,
+        last_sync_at=last_sync,
+        available_data_types=available_types,
+    ).model_dump()
 
 
 async def _handle_sync_data(arguments: dict) -> dict:
@@ -102,7 +208,12 @@ async def _handle_sync_data(arguments: dict) -> dict:
     types_synced = []
     for data_type in data_types:
         try:
-            result = await sync_service.sync_data_type(data_type=data_type, start_date=arguments.get("start_date"), end_date=arguments.get("end_date"), force_full=arguments.get("force_full_sync", False))
+            result = await sync_service.sync_data_type(
+                data_type=data_type,
+                start_date=arguments.get("start_date"),
+                end_date=arguments.get("end_date"),
+                force_full=arguments.get("force_full_sync", False),
+            )
             total_added += result.get("added", 0)
             total_updated += result.get("updated", 0)
             total_skipped += result.get("skipped", 0)
@@ -110,13 +221,32 @@ async def _handle_sync_data(arguments: dict) -> dict:
         except Exception as e:
             logger.error(f"Failed to sync {data_type}: {e}")
     finished_at = datetime.utcnow()
-    return {"status": "ok", "sync_id": sync_id, "started_at": started_at.isoformat(), "finished_at": finished_at.isoformat(), "records_added": total_added, "records_updated": total_updated, "records_skipped": total_skipped, "data_types_synced": types_synced}
+    return {
+        "status": "ok",
+        "sync_id": sync_id,
+        "started_at": started_at.isoformat(),
+        "finished_at": finished_at.isoformat(),
+        "records_added": total_added,
+        "records_updated": total_updated,
+        "records_skipped": total_skipped,
+        "data_types_synced": types_synced,
+    }
 
 
 async def _handle_get_profile() -> dict:
     if not adapter or not adapter.is_connected():
         return {"status": "error", "error": "Not connected to data source"}
-    return QueryResponse(status="ok", source=config.mode if config else "unknown", data={"profile": {"user_id": adapter.get_user_id() or "unknown", "timezone": config.timezone if config else "UTC", "devices": []}}).model_dump()
+    return QueryResponse(
+        status="ok",
+        source=config.mode if config else "unknown",
+        data={
+            "profile": {
+                "user_id": adapter.get_user_id() or "unknown",
+                "timezone": config.timezone if config else "UTC",
+                "devices": [],
+            }
+        },
+    ).model_dump()
 
 
 async def _handle_get_daily_summary(arguments: dict) -> dict:
@@ -133,24 +263,45 @@ async def _handle_get_daily_summary(arguments: dict) -> dict:
 async def _handle_query_metric_series(arguments: dict) -> dict:
     if not query_service:
         return {"status": "error", "error": "Query service not initialized"}
-    series = query_service.get_metric_series(metric=arguments["metric"], start_date=arguments["start_date"], end_date=arguments["end_date"], granularity=arguments.get("granularity", "day"), aggregation=arguments.get("aggregation", "sum"))
-    return QueryResponse(status="ok", source="cache", data={"metric": arguments["metric"], "series": series}).model_dump()
+    series = query_service.get_metric_series(
+        metric=arguments["metric"],
+        start_date=arguments["start_date"],
+        end_date=arguments["end_date"],
+        granularity=arguments.get("granularity", "day"),
+        aggregation=arguments.get("aggregation", "sum"),
+    )
+    return QueryResponse(
+        status="ok", source="cache", data={"metric": arguments["metric"], "series": series}
+    ).model_dump()
 
 
 async def _handle_query_heart_rate(arguments: dict) -> dict:
     if not query_service:
         return {"status": "error", "error": "Query service not initialized"}
-    samples = query_service.get_heart_rate_samples(start_date=arguments["start_date"], end_date=arguments["end_date"], sample_type=arguments.get("sample_type"), limit=arguments.get("limit"))
-    return QueryResponse(status="ok", source="cache", data={"samples": samples, "count": len(samples)}).model_dump()
+    samples = query_service.get_heart_rate_samples(
+        start_date=arguments["start_date"],
+        end_date=arguments["end_date"],
+        sample_type=arguments.get("sample_type"),
+        limit=arguments.get("limit"),
+    )
+    return QueryResponse(
+        status="ok", source="cache", data={"samples": samples, "count": len(samples)}
+    ).model_dump()
 
 
 async def _handle_query_body_measurements(arguments: dict) -> dict:
     if not query_service:
         return {"status": "error", "error": "Query service not initialized"}
-    measurements = query_service.get_body_measurements(start_date=arguments["start_date"], end_date=arguments["end_date"], metrics=arguments.get("metrics"))
+    measurements = query_service.get_body_measurements(
+        start_date=arguments["start_date"],
+        end_date=arguments["end_date"],
+        metrics=arguments.get("metrics"),
+    )
     if arguments.get("latest_only") and measurements:
         measurements = [measurements[-1]]
-    return QueryResponse(status="ok", source="cache", data={"measurements": measurements, "count": len(measurements)}).model_dump()
+    return QueryResponse(
+        status="ok", source="cache", data={"measurements": measurements, "count": len(measurements)}
+    ).model_dump()
 
 
 async def _handle_get_data_coverage(arguments: dict) -> dict:
@@ -167,7 +318,9 @@ async def main():
     if config.mode == "mi_fitness_cloud":
         user_id, pass_token = load_mi_fitness_token()
         if user_id and pass_token:
-            adapter = MiFitnessCloudAdapter(user_id=user_id, pass_token=pass_token, region=config.region)
+            adapter = MiFitnessCloudAdapter(
+                user_id=user_id, pass_token=pass_token, region=config.region
+            )
             if await adapter.connect():
                 logger.info("Connected to Mi Fitness cloud API")
             else: