feat: initial alpha scaffold — FastAPI + MCP + pgvector

Implements v0.0.1 of OpenBrain:

- FastAPI REST API (capture, search, recent, stats) with Bearer auth
- MCP server (streamable HTTP at /mcp) exposing all 4 tools
- pgvector schema (vector(1024) for bge-m3)
- asyncpg connection pool with lazy init + graceful close
- Ollama embedding client with fallback (stores thought without vector if Ollama unreachable)
- Woodpecker CI pipeline (lint + kaniko build + push to Gitea registry)
- Portainer/Swarm deployment compose
- Mosaic framework files: AGENTS.md, PRD.md, TASKS.md, scratchpad

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/models.py

@@ -0,0 +1,39 @@
+from datetime import datetime
+from typing import Any
+from pydantic import BaseModel
+
+
+class CaptureRequest(BaseModel):
+    content: str
+    source: str = "unknown"
+    metadata: dict[str, Any] = {}
+
+
+class Thought(BaseModel):
+    id: str
+    content: str
+    source: str
+    metadata: dict[str, Any]
+    created_at: datetime
+    embedded: bool
+
+
+class SearchRequest(BaseModel):
+    query: str
+    limit: int = 10
+    source: str | None = None
+
+
+class SearchResult(BaseModel):
+    id: str
+    content: str
+    source: str
+    similarity: float
+    created_at: datetime
+    metadata: dict[str, Any]
+
+
+class Stats(BaseModel):
+    total_thoughts: int
+    embedded_count: int
+    sources: list[dict[str, Any]]