diff --git a/.github/workflows/weekly-index.yml b/.github/workflows/weekly-index.yml
index 17071c7..11c78bb 100644
--- a/.github/workflows/weekly-index.yml
+++ b/.github/workflows/weekly-index.yml
@@ -14,6 +14,9 @@ jobs:
       JIXIA_REPO: https://github.com/frenzymath/jixia
       MODULE_NAMES: Physlib
       DRY_RUN: 'false'
+      # Each jixia worker loads ~2-3 GB of Mathlib; cap concurrency so the
+      # runner (16 GB) doesn't get OOM-killed during the load step.
+      JIXIA_MAX_WORKERS: '2'
       CHROMA_PATH: chroma
       CONNECTION_STRING: ${{ secrets.DATABASE_URL }}
       GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
diff --git a/database/jixia_db.py b/database/jixia_db.py
index f57e4f6..1601fd5 100644
--- a/database/jixia_db.py
+++ b/database/jixia_db.py
@@ -176,12 +176,18 @@ def topological_sort():
     with conn.cursor() as cursor:
         lean_sysroot = Path(os.environ["LEAN_SYSROOT"])
         lean_src = lean_sysroot / "src" / "lean"
+        # Each jixia worker loads the full Mathlib environment (~2-3 GB), so the
+        # default thread count (CPUs + 4) can exhaust memory and get the process
+        # OOM-killed. Cap it via JIXIA_MAX_WORKERS in memory-constrained CI.
+        max_workers_env = os.environ.get("JIXIA_MAX_WORKERS")
+        max_workers = int(max_workers_env) if max_workers_env else None
         all_modules = []
         for d in project.root, lean_src:
             results = project.batch_run_jixia(
                 base_dir=d,
                 prefixes=prefixes,
                 plugins=["module", "declaration", "symbol"],
+                max_workers=max_workers,
             )
             modules = [r[0] for r in results]
             load_module(modules, d)