diff --git a/FOUNDATION.md b/FOUNDATION.md index 80234f1d..aa10d977 100644 --- a/FOUNDATION.md +++ b/FOUNDATION.md @@ -131,44 +131,4 @@ Staying in our lane means we can be embedded inside IDEs, AI agents, CI pipeline --- -## Competitive Position - -As of February 2026, codegraph is **#7 out of 22** in the code intelligence tool space (see [COMPETITIVE_ANALYSIS.md](./generated/competitive/COMPETITIVE_ANALYSIS.md)). - -Six tools rank above us on feature breadth and community size. But none of them can answer yes to all three questions: - -1. **Can you rebuild the graph on every commit in a large codebase?** — Only codegraph has incremental builds. Everyone else re-indexes from scratch. -2. **Does the core pipeline work with zero API keys and zero cost?** — Tools like code-graph-rag and autodev-codebase require cloud APIs for core features. Codegraph's full graph pipeline is local and costless. -3. **Can you optionally enhance with your LLM provider?** — Local-only tools (CKB, axon, arbor) have no AI enhancement path. Cloud-dependent tools force it. Only codegraph makes it optional. - -| What competitors force you to choose | What codegraph gives you | -|--------------------------------------|--------------------------| -| Fast local analysis **or** AI-powered features | Both — zero-cost core + optional LLM layer | -| Full re-index on every change **or** stale graph | Always-current graph via incremental builds | -| Code goes to multiple cloud services **or** no AI at all | Code goes only to the one provider you chose | -| Docker + Python + external DB **or** nothing works | `npm install` and done | - -Our path to #1 is not feature parity with every competitor. It's being **the only code intelligence tool where the graph is always current, works at zero cost, and optionally gets smarter with the LLM you already use.** - ---- - -## Landscape License Overview - -How the competitive field is licensed (relevant for understanding what's available to learn from, fork, or integrate): - -| License | Count | Projects | -|---------|-------|----------| -| **MIT** | 10 | [code-graph-rag](https://github.com/vitali87/code-graph-rag), [glimpse](https://github.com/seatedro/glimpse), [arbor](https://github.com/Anandb71/arbor), [codexray](https://github.com/NeuralRays/codexray), [codegraph-cli](https://github.com/al1-nasir/codegraph-cli), [Bikach/codeGraph](https://github.com/Bikach/codeGraph), [repo-graphrag-mcp](https://github.com/yumeiriowl/repo-graphrag-mcp), [code-context-mcp](https://github.com/RaheesAhmed/code-context-mcp), [shantham/codegraph](https://github.com/shantham/codegraph), [khushil/code-graph-rag](https://github.com/khushil/code-graph-rag) | -| **Apache-2.0** | 2 | **[@optave/codegraph](https://github.com/optave/codegraph)** (us), [loregrep](https://github.com/Vasu014/loregrep) | -| **Custom/Other** | 1 | [CodeMCP/CKB](https://github.com/SimplyLiz/CodeMCP) (non-standard license) | -| **No license** | 9 | [axon](https://github.com/harshkedia177/axon), [autodev-codebase](https://github.com/anrgct/autodev-codebase), [Claude-code-memory](https://github.com/Durafen/Claude-code-memory), [claude-context-local](https://github.com/anasdayeh/claude-context-local), [CodeInteliMCP](https://github.com/rahulvgmail/CodeInteliMCP), [MCP_CodeAnalysis](https://github.com/0xjcf/MCP_CodeAnalysis), [0xd219b/codegraph](https://github.com/0xd219b/codegraph), [badger-graph](https://github.com/floydw1234/badger-graph), [CodeRAG](https://github.com/m3et/CodeRAG) | - -**Key implications:** -- MIT-licensed projects (10/22) are fully open — their approaches, algorithms, and code can be studied and adapted freely -- 9 projects have **no license at all**, meaning they are proprietary by default under copyright law — their code cannot legally be copied or forked, even though it's publicly visible on GitHub -- CKB (CodeMCP) has a custom license that should be reviewed before any integration or inspiration -- Our Apache-2.0 license provides patent protection to users (stronger than MIT) while remaining fully open source — a deliberate choice for enterprise adoption - ---- - -*This document should be revisited when the competitive landscape shifts meaningfully, or when a proposed feature contradicts one of the core principles above.* +*This document should be revisited when a proposed feature contradicts one of the core principles above.*