The agent-native VCS
Have AI agents write code 10x faster — by skipping codebase rediscovery.
Coding agents spend 90% of their time waiting for files to read: scanning thousands of lines just to find a function definition, grepping names, and rebuilding context. Throughput Lines of Code Per Day indexes your workspace inside the version control system and hands agents instant, structured answers. The feedback loop drops from minutes to seconds, multiplying your agent fleets' code-writing speed. Saving 10.7× on context tokens is just a side effect.
Pillars
HOW WE ACHIEVE MASSIVE AGENT CODE-WRITING THROUGHPUT WITH 10.7x TOKEN REDUCTION
Codebase awareness in milliseconds. Stop wasting 90% of execution time waiting for agents to parse thousands of lines of context just to find a single reference.
- ▸Sub-second context assembly gets answers to your agent instantly, slashing feedback delays.
- ▸Compact 1,700-token outlines instead of 5,000-token files mean models read and respond 3x faster.
- ▸Live Dependency Graph resolves symbol relationships instantly to avoid cloud API network round-trip lag.
Hammer Server ensures our throughput guarantees by allowing parallel edits without collision lag. Multiple agents can write code to the same checkout in parallel, multiplying team output without workspace corruption or manual merge overhead.
- ▸Concurrent agent checkouts let fleets write code in parallel rather than blocking each other in line queues.
- ▸Real-time CRDT workspace merging converges edits instantly without manual git conflict-resolution cycles.
- ▸To secure our throughput guarantees, agent writes are batched and synced to GitHub in a way that won't get you throttled.
Anvil Pods provide a harness for your agent and subagents that removes local CPU, RAM, and hard drive constraints. Keep local execution nodes fully responsive while fleets of agents compile, build, and test concurrently in the cloud.
- ▸Eliminate local bottlenecks so compiling, building, or testing agent code never slows down agent fleet throughput.
- ▸Offload compute-heavy builds to cloud-hosted Anvil Pods that spin up in milliseconds for instant test execution.
- ▸Run fifty agent tasks concurrently without running out of RAM, CPU, or disk space on local worker environments.
Our TLCPD MCP intelligently decides whether you need a Hammer Server or Anvil Pod and spins them up to keep you from slowing down.
Benefit: WAYYY Cheaper than a Claude Max 20x token plan with WAY more work done faster before you token max!
Install
Up and running in 10 minutes or less!
gan v0.1.1 ships as tarballs for macOS (Apple silicon) and Linux (x86_64). Every release publishes SHA256SUMS next to the artifacts — verify before you extract, the same way you'd want your auditors to.
# macOS (Apple silicon) curl -LO https://github.com/S7-Works/ganvil/releases/download/v0.1.1/ganvil-v0.1.1-aarch64-apple-darwin.tar.gz # Linux (x86_64) curl -LO https://github.com/S7-Works/ganvil/releases/download/v0.1.1/ganvil-v0.1.1-x86_64-unknown-linux-gnu.tar.gz # verify against the published checksums, then install curl -LO https://github.com/S7-Works/ganvil/releases/download/v0.1.1/SHA256SUMS shasum -a 256 -c --ignore-missing SHA256SUMS # sha256sum -c on Linux tar xzf ganvil-v0.1.1-*.tar.gz install ganvil-v0.1.1-*/gan ganvil-v0.1.1-*/gv ~/.local/bin/
The tarball carries two binaries: gan, the CLI, and gv, its helper. Then gan import any repo and point your agent at gan mcp.
Zero Friction Setup
Plug Throughput Lines of Code Per Day directly into your existing agent.
TLCPD implements the open Model Context Protocol (MCP) standard. Connecting it to Cursor, Claude Code, or any other agent client takes less than 30 seconds.
For Claude Desktop
Add the server config to the Claude Desktop application configuration file:
// ~/Library/Application Support/
// Claude/claude_desktop_config.json
{
"mcpServers": {
"ganvil": {
"command": "ganvil-mcp",
"env": {
"GANVIL_INDEX_TOKEN": "gv_pat_YOUR_TOKEN"
}
}
}
}For Claude Code
Register the server in your global tool configuration:
// ~/.code_mcp_config.json
{
"mcpServers": {
"ganvil": {
"command": "ganvil-mcp",
"env": {
"GANVIL_INDEX_TOKEN": "gv_pat_YOUR_TOKEN"
}
}
}
}For Cursor
Open Cursor Settings ➔ Features ➔ MCP, click "+ New MCP Server", and enter:
| Name | Ganvil |
| Type | command |
| Command | ganvil-mcp |
| Env Var | GANVIL_INDEX_TOKEN = gv_pat_... |
GANVIL_INDEX_TOKEN environment variable in your editor configuration.Your VCS is the knowledge graph. No sidecar indexer.
Sidecar graph tools proved the demand, then went stale between runs. TLCPD makes the graph a property of the repository — incremental, versioned, and queryable at any commit.