From 2a4a70e63641b6638d54e69f385b2b3449b78ba9 Mon Sep 17 00:00:00 2001
From: Nova <nova@Novas-Mac-mini.local>
Date: Mon, 9 Feb 2026 12:57:09 +0000
Subject: [PATCH] fix(mcp): chunk documents before reranking in query tool

The MCP query tool was passing full document bodies to the reranker,
which crashes on large documents (e.g. session transcripts >500KB)
with 'input lengths exceed the context size' errors, and can cause
Bun to segfault under memory pressure.

The CLI querySearch already chunks documents and picks the best chunk
per document before reranking. This applies the same approach to the
MCP query tool: chunk each candidate, select the best chunk via
keyword overlap, and rerank chunks instead of full bodies.
---
 src/mcp.ts | 26 ++++++++++++++++++++++++--
 1 file changed, 24 insertions(+), 2 deletions(-)

diff --git a/src/mcp.ts b/src/mcp.ts
index aa092048..d04f44af 100644
--- a/src/mcp.ts
+++ b/src/mcp.ts
@@ -15,6 +15,7 @@ import {
   createStore,
   reciprocalRankFusion,
   extractSnippet,
+  chunkDocument,
   DEFAULT_EMBED_MODEL,
   DEFAULT_QUERY_MODEL,
   DEFAULT_RERANK_MODEL,
@@ -403,10 +404,31 @@ You can also access documents directly via the \`qmd://\` URI scheme:
       const fused = reciprocalRankFusion(rankedLists, weights);
       const candidates = fused.slice(0, 30);
 
-      // Rerank
+      // Rerank — chunk documents first to avoid exceeding reranker context limits.
+      // Pick the best chunk per document using keyword overlap (matches CLI querySearch behaviour).
+      const queryTerms = query.toLowerCase().split(/\s+/).filter(t => t.length > 2);
+      const chunksToRerank: { file: string; text: string }[] = [];
+      for (const cand of candidates) {
+        const chunks = chunkDocument(cand.body);
+        if (chunks.length === 0) {
+          chunksToRerank.push({ file: cand.file, text: cand.body.slice(0, 2000) });
+          continue;
+        }
+        let bestIdx = 0;
+        let bestScore = -1;
+        for (let i = 0; i < chunks.length; i++) {
+          const chunkLower = chunks[i]!.text.toLowerCase();
+          const score = queryTerms.reduce((acc, term) => acc + (chunkLower.includes(term) ? 1 : 0), 0);
+          if (score > bestScore) {
+            bestScore = score;
+            bestIdx = i;
+          }
+        }
+        chunksToRerank.push({ file: cand.file, text: chunks[bestIdx]!.text });
+      }
       const reranked = await store.rerank(
         query,
-        candidates.map(c => ({ file: c.file, text: c.body })),
+        chunksToRerank,
         DEFAULT_RERANK_MODEL
       );