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# graph > **⚙️ Graph reasoning requires MemMesh hosted mode.** Building the graph works locally: `memory_extract_pending` → `memory_commit_extraction` populate typed entities/edges. Multi-hop **reasoning/traversal** (`memory_graph_reason`, `memory_query_graph`, `memory_prefetch_related`) runs on the hosted engine — set your `mm-` API key. If those return "unknown tool" on a local install, say so and use `search` over the extracted entities instead. MemMesh links memories into a knowledge graph whose edges are **bi-temporal** (each has `valid_from` / `valid_to`). That enables answers a flat store can't give. ## Multi-hop reasoning Answer questions that require chaining edges — "who acquired the company Sarah founded": ```jsonc { "name": "memory_graph_reason", "arguments": { "anchorEntityId": "<entity id>", "maxHops": 3, "maxPaths": 20 } } ``` Returns ranked paths (scored by edge weight × recency). The anchor is an entity id — resolve names to ids via a graph query first. ## Point-in-time — what did we believe then? ```jsonc { "name": "memory_query_graph", "arguments": { "subjectId": "<entity id>", "asOf": "2026-01-01T00:00:00Z" } } ``` Omit `asOf` for the current view. This reconstructs the graph as it stood on any date — the bi-temporal record, not just the latest state. ## Anticipatory retrieval (spreading activation) Given the memories a session is working with, surface what's most likely needed next: ```jsonc { "name": "memory_prefetch_related", "arguments": { "seedMemoryIds": ["<id>","<id>"], "limit": 10 } } ``` ## Building the graph Edges come from client-LLM extraction — the engine hands you a prompt, your own model extracts entities/edges, you commit them (zero engine-side LLM cost): ```jsonc { "name": "memory_extract_pending", "arguments": { "projectId": "<repo>", "limit": 10 } } // run each prompt through your model, then: { "name": "memory_commit_extraction", "arguments": { "memoryId": "…", "contentHash": "…", "entities": [...], "edges": [...] } } ``` Run this loop until `extract_pending` returns empty to fully populate the graph for reasoning.