GrapeRoot
June 11, 2026 · View on GitHub
graperoot.dev · Docs · Benchmarks · Pro · Discord · Troubleshooting
A context engine that makes Claude Code, Codex CLI, Gemini CLI, Cursor, OpenCode, and GitHub Copilot 30-45% cheaper without sacrificing quality. It builds a semantic graph of your codebase and pre-loads the right files into every prompt — so your AI spends tokens reasoning, not exploring.
Works on macOS, Linux, and Windows. Supports any project size.
Supports TypeScript, JavaScript, Python, Go, Swift, Rust, Java, Kotlin, C#, Ruby, and PHP.
Join the community: discord.com/invite/YwKdQATY2d
How It Works
You run: dgc /path/to/project
↓
1. Project scanned → semantic graph built (files, symbols, imports)
2. You ask a question
3. Graph identifies the relevant files → packs them into context
4. Claude gets your question + the right code already loaded
5. Fewer turns, fewer tokens, better answers
Token savings compound across a session. The graph remembers which files were read, edited, and queried — each turn gets cheaper.
Results
Benchmarked across 80+ prompts (5 complexity levels) on a real-world full-stack app. Full results at graperoot.dev/benchmarks.
| Metric | Without Dual-Graph | With Dual-Graph |
|---|---|---|
| Avg cost per prompt | $0.46 | $0.27 |
| Avg turns | 16.8 | 10.3 |
| Avg response time | 186s | 134s |
| Quality (regex scorer) | 82.7/100 | 87.1/100 |
Cost wins on 16 out of 20 prompts. Quality equal or better on all complexity levels.
Install
Full setup guide at graperoot.dev/setup.
macOS / Linux:
curl -sSL https://raw.githubusercontent.com/kunal12203/Codex-CLI-Compact/main/install.sh | bash
source ~/.zshrc # or ~/.bashrc / ~/.profile
Windows (PowerShell):
irm https://raw.githubusercontent.com/kunal12203/Codex-CLI-Compact/main/install.ps1 | iex
Windows (Scoop):
scoop bucket add dual-graph https://github.com/kunal12203/scoop-dual-graph
scoop install dual-graph
Prerequisites: Python 3.10+, Node.js 18+, Claude Code or Codex CLI. The installer detects missing tools and offers to install them via winget (Windows) or homebrew (macOS).
Usage
⚠️ Important: Always use
dgc(notclaudedirectly) to ensure the MCP server is running. Runningclaudealone will result in "MCP Server Connection Failed" errors.
Claude Code (dgc)
dgc # scan current directory, launch Claude
dgc /path/to/project # scan a specific project
dgc /path/to/project "fix the login bug" # start with a prompt
Codex CLI (dg)
dg # scan current directory, launch Codex
dg /path/to/project # scan a specific project
dg /path/to/project "add tests" # start with a prompt
Other AI Assistants (graperoot)
You can also use the graperoot command directly with any supported assistant:
graperoot . # current directory, default (Claude)
graperoot . --cursor # Cursor
graperoot . --gemini # Gemini CLI
graperoot . --opencode # OpenCode
graperoot . --copilot # GitHub Copilot
graperoot . --antigravity # Google Antigravity
graperoot . --codex # Codex CLI
graperoot /path/to/project --cursor # specific project
graperoot /path/to/project --gemini "add tests" # with a prompt
Or via the dgc / dg aliases with an assistant flag:
dgc --gemini /path/to/project # Gemini CLI
dgc --cursor /path/to/project # Cursor
dgc --opencode /path/to/project # OpenCode
dgc --copilot /path/to/project # GitHub Copilot
Typo detection is built in — --claud or --gemi will suggest the correct flag instead of silently failing.
Windows
dgc . # from inside the project directory
dgc "D:\projects\my-app" # any drive, any path
dg "C:\work\backend" # Codex CLI
dgc --gemini "D:\projects\app" # Gemini CLI on Windows
What It Does Under the Hood
- Scans your project — extracts files, functions, classes, import relationships into a local graph. Supports TS/JS, Python, Go, Swift, Rust, Java, Kotlin, C#, Ruby, and PHP.
- Pre-loads context — when you ask a question, the graph ranks relevant files and packs them into the prompt before Claude sees it. No extra tool calls needed.
- Remembers across turns — files you've read or edited are prioritized in future turns. Context compounds.
- MCP tools available — Claude can still explore the codebase via graph-aware tools (
graph_read,graph_retrieve,graph_neighbors, etc.) when it needs to go deeper.
All processing is local. No code leaves your machine.
Data & Files
All data lives in <project>/.dual-graph/ (gitignored automatically).
| File | Description |
|---|---|
info_graph.json | Semantic graph of the project: files, symbols, edges |
chat_action_graph.json | Session memory: reads, edits, queries, decisions |
context-store.json | Persistent store for decisions/tasks/facts across sessions |
mcp_server.log | MCP server logs |
Global files in ~/.dual-graph/:
| File | Description |
|---|---|
dgc.ps1 / dg.ps1 | Launcher scripts (auto-updated) |
venv/ | Python virtual environment for dependencies |
version.txt | Current installed version |
Configuration
All optional, via environment variables:
| Variable | Default | Description |
|---|---|---|
DG_HARD_MAX_READ_CHARS | 4000 | Max characters per file read |
DG_TURN_READ_BUDGET_CHARS | 18000 | Total read budget per turn |
DG_FALLBACK_MAX_CALLS_PER_TURN | 1 | Max fallback grep calls per turn |
DG_RETRIEVE_CACHE_TTL_SEC | 900 | Retrieval cache TTL (15 min) |
DG_MCP_PORT | auto (8080-8099) | Force a specific MCP server port |
Context Store
Decisions, tasks, and facts from your sessions are persisted in .dual-graph/context-store.json and re-injected at the start of the next session. This gives Claude continuity across conversations.
You can also create a CONTEXT.md in your project root for free-form session notes.
Token Tracking
A token-counter dashboard is registered automatically with Claude Code:
http://localhost:8899
Usage from inside a Claude session:
count_tokens({text: "<content>"}) # estimate tokens before reading
get_session_stats() # running session cost
Self-Update
The launcher checks for updates on every run and auto-updates if a new version is available. No manual intervention needed.
Current version: 3.9.96
Troubleshooting
"MCP Server Connection Failed" or "HTTP 404: Not Found"
Cause: The dual-graph MCP server isn't running. This happens when running claude directly instead of through dgc.
Solution: Always use dgc instead of claude:
# ❌ Don't run:
claude
# ✅ Run this:
dgc
dgc /path/to/project
The dgc launcher automatically starts the MCP server and registers it with Claude Code.
If the error persists:
-
Clean up stale configs:
claude mcp remove dual-graph claude mcp remove token-counter --scope user -
Run dgc again (it will re-register automatically):
dgc -
Check if the server started:
# Verify MCP server is running: lsof -i :8080-8099 | grep python # Check logs: cat .dual-graph/run/claude/mcp_server.log -
Fresh install (if nothing else works):
rm -rf ~/.dual-graph claude mcp remove dual-graph 2>/dev/null curl -sSL https://raw.githubusercontent.com/kunal12203/Codex-CLI-Compact/main/install.sh | bash source ~/.zshrc # or ~/.bashrc
MCP Server Won't Start
Check the logs:
cat .dual-graph/run/claude/mcp_server.log
Common issues:
- Port already in use: Set a custom port with
DG_MCP_PORT=8090 dgc - Python dependencies missing: Re-run installer or
pip install graperoot mcp uvicorn --upgrade - Permission errors: Check file permissions in
.dual-graph/
Session-Specific Issues
Resume not working? The MCP server is session-based — it stops when you exit. To resume with dual-graph:
dgc --resume <session-id>
Context not persisting? Check if .dual-graph/context-store.json exists and is writable.
Privacy & Security
- All project data stays local. Graphs, session data, and code never leave your machine.
- The only outbound calls are:
- Version check — fetches a version string (no project data).
- Heartbeat — sends a random install ID and
platformonly. No hardware fingerprinting, no file names, no code. - One-time feedback — optional rating after first day of use.
.dual-graph/is automatically added to.gitignore.
Uninstall
macOS / Linux:
rm -rf ~/.dual-graph
sed -i.bak '/\.dual-graph/d' ~/.zshrc ~/.bashrc 2>/dev/null
rm -rf .dual-graph .claude/settings.local.json
claude mcp remove token-counter --scope user 2>/dev/null
claude mcp remove dual-graph 2>/dev/null
rm -rf ~/.claude/token-counter
rm -f ~/.claude/token-counter-stop.sh
Windows (PowerShell):
Remove-Item "$env:USERPROFILE\.dual-graph" -Recurse -Force -ErrorAction SilentlyContinue
$p = [Environment]::GetEnvironmentVariable("PATH","User") -split ";" | Where-Object { $_ -notlike "*\.dual-graph*" }
[Environment]::SetEnvironmentVariable("PATH", ($p -join ";"), "User")
Remove-Item ".dual-graph" -Recurse -Force -ErrorAction SilentlyContinue
Remove-Item ".claude\settings.local.json" -Force -ErrorAction SilentlyContinue
claude mcp remove token-counter --scope user 2>$null
claude mcp remove dual-graph 2>$null
Remove-Item "$env:USERPROFILE\.claude\token-counter" -Recurse -Force -ErrorAction SilentlyContinue
Remove-Item "$env:USERPROFILE\.claude\token-counter-stop.ps1" -Force -ErrorAction SilentlyContinue
The PATH/project commands remove the global install. Run the project-local commands inside each project you used dual-graph with.
Contributing
The launcher scripts (bin/) are open source under Apache 2.0. PRs are welcome — bug fixes, new AI assistant support, install improvements, docs.
Note: The graph engine (graperoot) is a separate proprietary component distributed via PyPI. The launcher scripts and tooling in this repo are fully open source; the core graph intelligence is not. See graperoot.dev/graperoot-pro for Pro features.
Community
Have a question, found a bug, or want to share feedback?
Join the Discord: discord.com/invite/YwKdQATY2d
- Get help with setup
- Report bugs
- Share workflows
- Follow releases
Acknowledgements
A huge thank you to everyone who used early versions of Dual-Graph and shared feedback through the telemetry program — your usage data helped us squash bugs and stabilize the tool into what it is today. We've now removed all telemetry in favor of full transparency.
Want to keep helping shape the project? Join the Discord or visit graperoot.dev.
Star History
License
The launcher scripts and tooling in this repository are licensed under the Apache License 2.0.
The graperoot graph engine (installed as a PyPI dependency) is proprietary and not covered by this license.