Same Answers, 63% Fewer Tokens

Ragtoolina gives your AI coding tools semantic understanding of your codebase. Precise context instead of file dumps — saving tokens, time, and money.

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Semantic Code Search

Find code by meaning, not keywords. Ask "where is authentication handled?" and get the actual auth module — not every file that mentions "auth". Results ranked by semantic relevance with sub-second response times.

Natural language queries across your entire codebase
Relevance-ranked results with confidence scores
Cross-file and cross-repo search
Understands intent, not just string matching

where is authentication handled?

src/auth/auth.service.tsvalidateUser()

L42-670.94

src/auth/guards/jwt.guard.tscanActivate()

L12-310.87

src/auth/strategies/local.strategy.tsvalidate()

L8-220.81

3 results in 24ms

MCP Protocol Integration

Ragtoolina speaks the Model Context Protocol natively. Claude Code, Cursor, Windsurf, and any MCP-compatible tool can query your semantic index — no plugins or extensions needed. Two lines of config and you're connected.

Works with Claude Code, Cursor, Windsurf, VS Code, Firebender
Zero-config local MCP server
Tools: search, find_symbol, get_symbol_tree, and 50+ more
Transparent — your workflow doesn't change

.cursor/mcp.json

{
  "mcpServers": {
    "ragtoolina": {
      "command": "ragtoolina",
      "args": ["mcp"]
    }
  }
}

63% Fewer Tokens

By sending only semantically relevant context instead of raw file dumps, Ragtoolina cuts token usage by 63% on average — with no loss in answer quality. Less noise means your AI assistant focuses on code that matters.

2.6x cost reduction on AI coding sessions
Same or better answer quality (benchmarked)
53% faster response times from less input
ROI from day one at $19/month

QueryWithoutWithSaved

Auth flow12,4004,20066%

API routes8,9003,10065%

DB schema6,3002,50060%

Average9,2003,26763%

Integrations

Index more than just code. Connect GitHub, Jira, Confluence, and Azure DevOps to bring requirements, architecture docs, and team knowledge into your AI's context. Changes sync automatically.

GitHub — repos including private and Enterprise
Jira — issues and comments for requirements context
Confluence — technical docs and architecture decisions
Azure DevOps — repositories and work items

Team Integrations4 connected

GitHub

Synced

Jira

Synced

Confluence

Synced

Azure DevOps

Connect

Team Indexes

Share a single semantic index across your entire team. New hires get instant codebase understanding. Cross-team questions get accurate answers. Per-member usage tracking keeps costs visible.

Shared indexes update in real-time for all members
Role-based access: Owner, Admin, Member
Per-member embedding usage analytics
Bulk invite via CSV for Enterprise teams

aurora-web team4 members

Sarah ChenOwner

12.4k tokens

Alex RiveraAdmin

8.7k tokens

Jordan LeeMember

15.2k tokens

Taylor KimMember

6.1k tokens

Privacy First

Your source code never leaves your machine. Ragtoolina processes files locally and stores only vector embeddings in the cloud — mathematical representations that can't be reversed into code. Encrypted in transit and at rest.

Raw source code stays on your machine
Only vector embeddings stored in the cloud
TLS 1.2+ encryption in transit
Embeddings encrypted at rest

Your Codestays local

embed

Vectorsencrypted

query

AI Toolcontext

Raw source code never leaves your machine

macOS Native App

Ragtoolina runs as a lightweight macOS menu bar app. Index projects, manage servers, and monitor sync status without leaving your workflow. Incremental re-indexing keeps your context up to date as code changes.

Menu bar app — always running, never in the way
Incremental indexing after code changes
Multi-project support with independent indexes
Team knowledge docs alongside code context

Ragtoolina

3 Servers

Projects

aurora-web

5,847 chunks743 files

payments-api

3,192 chunks428 files

vector-search

8,241 chunks1,312 files

Ready to Cut Your AI Coding Costs?

Free to start. Pro at $19/month. ROI from day one.

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