Compare AI tools

	Elicit S	GitNexus A	Perplexity S	Otter.ai B
Tagline	AI research assistant for academic literature.	An open-source, MCP-native knowledge graph engine that gives AI coding agents (Cursor, Claude Code, Windsurf) genuine structural awareness of your codebase before they touch a single line.	AI search done right. Cited answers, not chat theater.	Meeting transcription veteran. Cross-platform, team-friendly.
Category	Research	Coding	Research	Meetings
Pricing	Free + $12-$42/mo	Free (MIT open source)	Free + $20/mo Pro	Free + $17-$30/user/mo
Best for	Grad students, researchers, anyone doing literature reviews.	Developers working in large or unfamiliar codebases who want their AI coding agent to stop making confident, structurally blind edits — especially Claude Code power users.	Replacing Google for any question where you want a cited answer in seconds.	Teams on Windows/PC. Anyone needing cross-platform coverage.
Strengths	Searches 125M+ papers Extracts + synthesizes findings across papers Systematic review workflow	Pre-computes a full dependency graph (functions, imports, class inheritance, execution flows) via Tree-sitter ASTs — agents query structure, they don't guess at it Zero-server, privacy-first: CLI runs entirely locally with no network calls; browser UI processes code client-side and never uploads it Deepest Claude Code integration on the market: MCP tools + agent skills + PreToolUse/PostToolUse hooks that auto-enrich searches and auto-reindex after commits One global MCP server handles multiple indexed repos — set up once with npx gitnexus setup and forget it detect_impact and generate_map MCP prompts give pre-commit blast-radius analysis and auto-generated Mermaid architecture docs	Sources every claim Fast, current answers Pro Search runs multi-step research Spaces for persistent context	Joins meetings as a bot (Zoom, Meet, Teams) Team sharing + search across transcripts Live captioning
Weaknesses	Academic-only Can hallucinate citations — verify everything	Browser-side RAG has hard ceilings: WASM heap limits constrain embedding model quality compared to server-side tools; monorepos or repos >50k files hit practical walls Community-built and not officially maintained — velocity and long-term support depend on contributor goodwill Claude Code gets the full integration experience; other editors (Windsurf, Cursor) get progressively less — value is uneven depending on your editor	Not a general chatbot Answers can be shallow on complex topics	Bot joining is intrusive UX feels dated
Kai's verdict	S-tier for academic research. Nothing else comes close for systematic reviews.	GitNexus solves a real and underappreciated problem: AI coding agents are syntactically fluent but architecturally blind, and plugging a pre-computed knowledge graph into the MCP layer is the right fix. 28k GitHub stars in days suggests the pain is widely felt — just go in knowing it's a community project, not a polished product. (Verdict pending Phi's full review.)	S-tier for search. I use it before Google now. If you're still Googling everything, try this for a week.	B-tier. Granola is better UX but Otter works everywhere. Pick based on your platform.
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