Vs · Cursor

Anvaya vs Cursor.

The best AI-native IDE against the memory-first terminal agent. Complementary layers, not substitutes.

Direct answer

Anvaya vs Cursor is a layer question, not a winner question. Cursor is the most polished AI IDE: best-in-class tab autocomplete, Composer multi-file edits with visual diffs, background agents, multi-model support, at $20–200/mo, cloud-processed, VS Code fork only. Anvaya is the terminal-first agent with compounding memory: Ollama-first and offline, 21 native tools, subagents, headless CI, and a local knowledge graph (typed nodes, decay, drift detection, outcome calibration) packing 2–4K tokens per turn instead of ~50K raw. Cursor wins inline daily editing; Anvaya wins autonomous refactors, private codebases, and knowledge that survives sessions. Most senior setups run both: Cursor for the edit loop, Anvaya for memory and depth, bridged over MCP.

The Table

Side by Side.

DimensionCursorAnvayaWinner
Primary surfaceIDE (VS Code fork)Terminal TUI + headlessDifferent layers
AutocompleteBest-in-class tabNone (agent-first)Cursor
Memory modelRules + index, retrievesTyped graph, calibratedAnvaya on compounding
AutonomyBackground agents (seq.)Subagents + swarm packsAnvaya on orchestration
Offline/privateCloudroutedFully localAnvaya
JetBrainsNoVia MCP-clients + CLINeither native
Entry price$20/mo$0 local loopAnvaya

Questions

Asked About the Two.

Q

Should I replace Cursor with Anvaya?

Usually no, they operate at different layers. Cursor owns inline editing: tab autocomplete, Composer multi-file diffs, the polished IDE loop. Anvaya owns memory and autonomy: terminal-first agentic runs plus a graph that compounds across sessions. The common pattern is Cursor for daily edits, Anvaya for deep refactors and cross-session knowledge.

Q

Can Cursor use Anvaya's memory?

Yes over MCP: point Cursor at Anvaya's memory server and its agent turns arrive with packed project memory (decisions, bug threads, conventions) instead of re-deriving them. One graph serves the IDE and the terminal.

Q

Which handles large codebases better?

Cursor's semantic codebase index is the most mature IDE-side retrieval available. Anvaya adds repomap PageRank plus pooled LSP diagnostics plus calibrated memory of past work in that codebase. For navigating what exists: Cursor. For remembering what was learned: Anvaya.

Q

What about privacy?

Cursor processes code in the cloud (SOC 2, enterprise tiers). Anvaya defaults to fully local: Ollama models, on-disk graph, offline capable. Regulated or NDA codebases that can't use cloud IDE features can still run Anvaya privately.

Run Agents That Fit On Your Laptop.

25.6 MB median RSS. 25 agents ran in parallel on a Core 2 Duo with 4 GB RAM. Hundreds on your machine. Zero cloud required on the Ollama path.

Get Started →Read the FAQ

Requires Rust/cargo to build from source. Linux and macOS today, Windows not yet supported. Pre-1.0, public beta. Pricing TBD.