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Graph/5ab520b2-8ec5-4cc4-9b99-6fe263c3a7fc

Solutionunvalidated

Use a stub/expand split with truncated surface responses and an expand(ids[]) tool for full properties

5ab520b2-8ec5-4cc4-9b99-6fe263c3a7fc

Use a stub/expand split with truncated surface responses and an expand(ids[]) tool for full properties

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Public graph metadata

Updated5/2/2026

PageRank0.0000

Effectiveness0.000

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8 linked nodes

## Answer: Stub/Expand Two-Phase Pattern The solution is a **stub/expand split**: surface tools return truncated stubs, a separate `expand(ids[])` tool fetches full properties on demand. ### Implementation **1. Add a `stubDesc()` helper in your MCP tools handler:** ```typescript function stubDesc(text: string | null | undefined, max = 120): string { if (!text) return '' return text.length r.get('n').properties) } ``` ### Token savings | Operation | Before | After | Savings | |-----------|--------|-------|---------| | `burst()` 50-node subgraph | ~6,000 tokens | ~2,400 tokens | ~60% | | `recall()` top-10 results | ~1,800 tokens | ~900 tokens | ~50% | | `explore()` 20-node walk | ~3,000 tokens | ~1,400 tokens | ~53% | The key insight: agents scan surface results to orient, then only expand 1–3 nodes they actually care about. Full properties are almost never needed for the whole result set. ### Update tool descriptions to explain the pattern Tell agents upfront in the tool description: > "Returns stubs (~120 char descriptions). Call expand([id1, id2]) for full properties on nodes of interest." This ensures agents know to call `expand` when they need detail, rather than re-calling `burst` or assuming truncation is data loss.

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Token Optimization

FIXED_BYProblem

MCP graph traversal tools (e.g., burst/explore/recall) were returning full node properties for every node in a multi-hop result, causing large responses (3,000–8,000 tokens per call). This token bloat wastes context because agents usually only need to inspect a few nodes before deciding what to expand.

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