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Backed byY Combinator

The knowledge graphcontrol plane forenterprise software.

Free plan, no card · run the open-source engine yourself

139,481Github stars
9.6MPyPI downloads
13.1MRepositories indexed
How it works

One map of the code

One graph across every repository and team, built once and kept current. Nobody re-learns the codebase by hand, and what one engagement learns carries into the next.


Answers with proof

Every answer is a path through the graph you can open, spanning code, docs, wikis and contracts. Evidence rather than opinion, for audited and regulated work.


See what breaks

Before the merge, the graph follows every edge to what a change breaks. The agent reads the graph instead of the repo, so the token bill buys answers.

Read the docs

Used by engineers at

Features

Understand your code. Know where to look next.

Build with code context, inspect reviews and supported verification, and recover shared repository knowledge.

Interactive graph

Dots represent parts of your code; lines show recorded connections. Select a function to see what uses it and open its source.

Fully on-device

Run the open-source engine and parsing stays on your machine: 33 tree-sitter grammars, no uploads, no telemetry.

Query, don’t grep

Give your assistant source-linked code context. In Cloud, add shared Memory with inspectable sources and history.

20+ assistants

Your assistant queries the graph over MCP, in Claude Code, Cursor, Copilot, and 14 more.

Cross-repo graph

One persistent graph across every repo, so answers follow owners across services.

PR review

graphify prs triages CI, review, and merge-conflict risk, learning from each merge.

Formal verification

Compare supported behavior changes and inspect the evidence. Coverage depends on the workflow and language.

Side by side

Graph, chunks or grep.

Four tools an enterprise shortlists, as each vendor documents them in October 2026.

See full comparison
Graphify
CapabilityGraphifyCodeRabbitGreptileSourcegraph
Differential verificationprove it or break itno formal verificationreview and runtime testssearch and batch changes
Cross-repo blast radiusevery connected repolinked repos, per PRup to 7 linked reposrefs, no verdict
Typed code graphpersistent, queryableper change (Codegraph)stored, used in reviewscross-repo (SCIP, opt-in)
Multi-hop reasoningnative traversalagentic, in reviews and chatagentic hopsagentic retrieval
Auditable answera path you can opencomments with evidencefindings, confidence scoresanswers list sources
Provenanceevery edge taggedBlast Radius only (beta)not documentedsearch and file sources
Deploymentcloud · self-run open sourceself-host, 500+ seatsself-host / air-gapcloud or self-host
Any AI assistantany MCP clientCLI and plugins, MCP clientMCP server + CLIMCP server (Enterprise)
Licenseopen core (Apache 2.0)proprietaryproprietaryproprietary

Try it on your own repo

$uv tool install graphifyy

Try for freeRequest a demo
Trust

Run it on your machine, or let us run it.

The open-source tool never sends your code anywhere. The hosted product is a choice, not the only way in.

How we think about security
  • On-device

    The command-line tool parses locally with 33 tree-sitter grammars and writes the graph to a file on your own disk.

  • No telemetry

    The tool sends no usage pings, no crash reports and no analytics. Nothing to opt out of, because nothing is sent.

  • Apache 2.0

    The whole source is Apache 2.0 on GitHub. You need not trust this page; read what the code does.

  • Yours to host

    Serve the graph over stdio or over HTTP on infrastructure you own, and on Enterprise run the whole thing there.

SOC 2 Type IIEngagement Started
Proof
FAQ

Frequently Asked Questions

Common questions about how Graphify works.

  • RAG splits your code into chunks, embeds them, and retrieves the top-k that look similar to your question. Graphify builds a real graph and traverses it, so every answer is an explicit path with file:line citations. There are no embeddings and no vector store. You follow the actual call and import edges instead of guessing which chunks are relevant.

  • That is your choice. The open-source engine parses code locally with tree-sitter, which is deterministic AST extraction with no model call and no telemetry, so nothing leaves your machine unless you point the non-code pass at a hosted model. The hosted product builds and keeps the same graph for you in the cloud, on the repositories you connect.

  • Yes. The hosted product at app.graphify.com has a Free plan with no card, and Pro and Teams by seat above it (those need a card). The open-source engine is free under Apache 2.0, runs on your own machine, and needs no account. Graph-aware review and formal verification are in every hosted plan, Free included. The early-access Enterprise layer adds self-hosting, SAML single sign-on and legacy migration.

  • 17, including Claude Code, Cursor, Copilot, Codex, Gemini CLI and Aider. Run graphify install --platform <name> for each assistant you use; bare graphify install sets up Claude Code. The graph is also served over an MCP server any client can query.

  • LSP answers one hop: where a symbol is defined, where it is referenced. A graph answers questions that span the codebase, such as what breaks if you change this, every path between two functions, and how a doc or config connects to the code. It is persistent, queryable by your assistant, and every edge carries a provenance tag.

  • ctags builds a flat symbol index for jump-to-definition. Sourcegraph is enterprise code search, run in its cloud or self-hosted. Graphify builds a typed graph your assistant traverses over CLI or MCP. It is not a symbol table and not a search box.

  • Yes, incrementally. A code change re-parses only the changed file through the local AST pass, with no re-embedding and no full re-index. Install the git hook and the graph rebuilds on every commit.

  • Yes. Code parsing is always local. Point the semantic pass at a local model such as Ollama, or any OpenAI-compatible server like vLLM, and nothing leaves the machine: tree-sitter on code, your local model on docs.

  • It can store embeddings as one signal on a node, but retrieval is a graph traversal rather than a similarity search. Results come back connected and explainable instead of as a ranked list of lookalike chunks.

Try Graphify now.

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