GitDB turns your codebase into a queryable surface for AI agents. They read the exact lines they need, swarm in parallel through pointer-sized handoffs, and remember what they learned — up to 95% fewer tokens per call. Engineers keep their editor; teams keep their CI/CD; you keep the bill in check.
The next decade of software will be written by teams of agents working in parallel, at machine speed. GitDB is the data layer built for that future — agent-native, multi-agent ready, and fast enough to keep up.
Forget cloning. GitDB gives your agents first-class tools to find a function, patch a file, or open a PR — all in single-digit milliseconds. They reason on the code that matters and skip the 9,000 tokens of file boilerplate.
Build a swarm of specialist agents that hand work off to each other through GitDB. Each handoff is a tiny pointer — file paths and line ranges, not raw code — so a 4,000-token handover collapses to about 15. The team gets more done, and the LLM bill barely moves.
Stop stitching together a code host, a vector database, an audit service, and a memory store. GitDB consolidates all of it on one engine — so your agents share context instead of paying to rebuild it on every call.
Agents don't need to read the whole file to patch one function — and they don't need to re-discover what they already learned. GitDB feeds your model exactly the code it asked for, then remembers what it figured out. Smaller inputs, smarter agents, a smaller invoice.
Agents read exact line ranges, not whole files. Semantic search and structured queries serve up only the code your model asked for.
Long-term agent memory means you stop paying to re-discover the same solution every time. Skills, decisions, and patterns stay learned.
Stack the two — smaller inputs and recallable memory — and a task that used to burn 20K tokens now costs about 2K. Same answer, ten times less spend.
Find code by what it does, not what it's called. Sub-millisecond vector search over every function in every commit.
gitdb_search_code("rate limit auth handler")
→ ranked matches across 12 repos in 0.3msFind a function by name, list every caller, or jump across modules — structured queries over a live AST index.
gitdb_find_function("process_payment")
gitdb_find_callers("auth_middleware")`self.handler.process()` gets resolved to the right definition across 20 modules — no more ambiguous grep hits.
There is no `git clone`, no ZIP export, no bulk repo download. Engineers open repos as `gitdb://…` workspaces in VS Code; agents pull line ranges through a tool API. Code lives in GitDB and nowhere else.
gitdb_read_lines("src/auth.py", 42, 60)
gitdb_write_lines("src/auth.py", 42, new_code)
gitdb_commit("feat: add rate limiting")Stray API keys, banned dependencies, and policy violations get caught before they ever land. Your standards run inside the database, so every contributor and every agent ships clean code by default.
Spec-writer, coder, reviewer, tester — a swarm of specialist agents shipping features in parallel. Each one has its own identity. Handoffs are pointer-sized (paths + line ranges), so the team stays cheap to run and easy to trace.
Join the private beta. Get early access to GitDB, Memory, Vector, and Embedded Robotics services.
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