feat(mcp): enhance search with intervention and eligibility dimensions

- search_direct() now uses structured query params (query.cond,
query.intr, query.term) instead of single query.term
- search_multi_variant() adds intervention-specific (variant 4) and
eligibility-keyword (variant 5) search variants
- search() (MCP path) includes interventions in query

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

trialpath/services/mcp_client.py

@@ -112,6 +112,8 @@ class ClinicalTrialsMCPClient:
             query_parts.append(anchors.subtype)
         if anchors.biomarkers:
             query_parts.extend(anchors.biomarkers)
+        if anchors.interventions:
+            query_parts.extend(anchors.interventions[:2])
 
         query = " ".join(query_parts)
 
@@ -283,24 +285,37 @@ class ClinicalTrialsMCPClient:
     async def search_direct(self, anchors: SearchAnchors) -> list[dict]:
         """Search ClinicalTrials.gov API v2 directly with retry.
 
-        Uses requests instead of httpx because ClinicalTrials.gov blocks
-        httpx via TLS fingerprinting (403 Forbidden).
-        Retries on ConnectionError/Timeout with exponential backoff.
+        Uses structured query parameters:
+        - query.cond: condition (+ subtype)
+        - query.intr: first intervention (drug name)
+        - query.term: eligibility keywords (ECOG, stage, biomarkers)
+
+        Falls back to query.term-only when new fields are absent (backward
+        compatible).
         """
         import requests
 
-        query_parts = [anchors.condition]
-        if anchors.biomarkers:
-            query_parts.append(anchors.biomarkers[0].split()[0])
-
-        query = " ".join(query_parts)
-        if len(query) > 100:
-            query = anchors.condition
+        # Build condition query (query.cond)
+        cond_parts = [anchors.condition]
+        if anchors.subtype:
+            cond_parts.append(anchors.subtype)
+        cond_query = " ".join(cond_parts)
 
         params: dict = {
-            "query.term": query,
+            "query.cond": cond_query,
             "pageSize": 50,
         }
+
+        # Intervention query (query.intr) — first drug name
+        if anchors.interventions:
+            params["query.intr"] = anchors.interventions[0]
+
+        # General term query (query.term) — eligibility keywords or biomarker fallback
+        if anchors.eligibility_keywords:
+            params["query.term"] = " ".join(anchors.eligibility_keywords)
+        elif anchors.biomarkers:
+            params["query.term"] = anchors.biomarkers[0].split()[0]
+
         if anchors.geography:
             params["query.locn"] = anchors.geography.country
 
@@ -349,9 +364,11 @@ class ClinicalTrialsMCPClient:
         """Fire multiple search variants in parallel for broader recall.
 
         Variants:
-        1. Full query (condition + biomarkers) -- high precision
+        1. Full query (condition + interventions + eligibility keywords)
         2. Condition-only query -- broader recall
         3. Per-biomarker queries (top 2) -- catches niche trials
+        4. Per-intervention queries -- finds drug-specific trials
+        5. Condition + eligibility keywords -- pre-filters by clinical features
 
         Results are merged and deduplicated by NCT ID.
         """
@@ -376,6 +393,26 @@ class ClinicalTrialsMCPClient:
                 bio_anchors.geography = anchors.geography
             queries.append(self.search_direct(bio_anchors))
 
+        # Variant 4: Per-intervention queries (drug-specific trials)
+        for intervention in (anchors.interventions or [])[:3]:
+            intr_anchors = SearchAnchors(
+                condition=anchors.condition,
+                interventions=[intervention],
+            )
+            if anchors.geography:
+                intr_anchors.geography = anchors.geography
+            queries.append(self.search_direct(intr_anchors))
+
+        # Variant 5: Condition + eligibility keywords (clinical feature pre-filter)
+        if anchors.eligibility_keywords:
+            elig_anchors = SearchAnchors(
+                condition=anchors.condition,
+                eligibility_keywords=anchors.eligibility_keywords,
+            )
+            if anchors.geography:
+                elig_anchors.geography = anchors.geography
+            queries.append(self.search_direct(elig_anchors))
+
         # Fire all variants in parallel
         results = await asyncio.gather(*queries, return_exceptions=True)