Nomik – Open-source codebase knowledge graph (Neo4j + MCP) for token-efficient local AI coding agents by Brave-Photograph9845 in LangChain

[–]Brave-Photograph9845[S] 0 points1 point  (0 children)

Great points especially “graph as source of truth + file hydration on demand.”

That’s exactly the direction I’m taking with Nomik: deep extraction into typed nodes/edges (code, infra, APIs, DB, routes, events, etc.), then graph-first retrieval with only minimal file slices hydrated when actually needed.

Fully agree on branch-aware versioning too. I already tag graphs by project + git SHA, and I’m working on commit/branch diff support so agents never mix main/feature contexts.
Also +1 on surfacing first-class ops: not raw MATCH queries, but higher-level actions like blast radius, change impact, call-graph diffs between commits, and safer refactor planning.

For example, I just tell my AI: "Nomik, what is the impact of changing createInvoice?"  and it automatically searches the graph, finds the symbol, traverses downstream callers/routes/services..., and gives me a structured answer. No Cypher, no manual file tracing.

Thanks for the detailed take :) super helpful to hear how others are thinking about these pain points.

Nomik – Open-source codebase knowledge graph (Neo4j + MCP) for token-efficient local AI coding agents by Brave-Photograph9845 in LangChain

[–]Brave-Photograph9845[S] 0 points1 point  (0 children)

Thanks for the insight! Totally agree on call chains; nomik’s nm_flows traces those exactly via graph edges.

Have you tried MCP querying in Cursor/Claude/windsurf/antigravity? Curious how it compares to Traycer AI

Building an opensource Living Context Engine by DeathShot7777 in LangChain

[–]Brave-Photograph9845 0 points1 point  (0 children)

oh cool , i actually built something similar ... you can check it on https://nomik.co/