fix tests for context and permalinks

src/basic_memory/mcp/tools/memory.py

@@ -0,0 +1,46 @@
+"""Discussion context tools for Basic Memory MCP server."""
+
+from typing import Optional
+
+from loguru import logger
+
+from basic_memory.mcp.async_client import client
+from basic_memory.mcp.server import mcp
+from basic_memory.schemas.memory import GraphContext, MemoryUrl
+
+
+@mcp.tool(
+    description="Build context from a memory:// URI to continue conversations naturally.",
+)
+async def build_context(
+    url: MemoryUrl,
+    depth: Optional[int] = 1,
+    timeframe: Optional[str] = "7d",
+    max_results: int = 10
+) -> GraphContext:
+    """Get context needed to continue a discussion.
+
+    This tool enables natural continuation of discussions by loading relevant context
+    from memory:// URIs. It uses pattern matching to find relevant content and builds
+    a rich context graph of related information.
+
+    Args:
+        ctx: MCP context
+        url: memory:// URI pointing to discussion content (e.g. memory://specs/search)
+        depth: How many relation hops to traverse (default: 2)
+        timeframe: How far back to look, e.g. "7d", "24h" (default: "7d")
+        max_results: The maximum number of results to return (default: 10)
+
+    Returns:
+        GraphContext containing:
+            - primary_entities: Directly matched content
+            - related_entities: Connected content via relations
+            - metadata: Context building info
+    """
+    logger.info(f"Building context from {url}")
+    # Map directly to the memory endpoint
+    memory_url = MemoryUrl.validate(url)
+    response = await client.get(
+        f"/memory/{memory_url.relative_path()}", params={"depth": depth, "timeframe": timeframe, "max_results": max_results}
+    )
+    return GraphContext.model_validate(response.json())