GSD GraphA modern, open source graph platform built for performance, flexibility, and scale.
Extract, normalize, connect, and query grounded local knowledge graphs from project docs, architecture decisions, and code — empowering AI coding agents with verified citations and zero cloud dependencies.
"Worktree isolation in Milestone 07 enforces sandbox constraints from ADR-12 before test verification executes in harness.spec.ts."
Built for Performance, Flexibility, & Scale
Knowledge graphs that don't require heavy cloud infrastructure, subscription fees, or complex cluster setups.
High Performance
Sub-millisecond local vector and graph traversals. Built to respond instantly inside agent execution loops without latency spikes.
Developer Friendly
Zero-config setup. Drop into any repository with 1 line, inspect with intuitive query syntax, or connect directly via MCP.
Scalable by Design
Local-first SQLite + vector indexing that scales effortlessly from small side projects to multi-million node monorepos.
100% Open Source
MIT licensed, completely local, zero telemetry, and zero cloud vendor lock-in. Your codebase knowledge remains strictly yours.
Explore GSD Graph in Action
Click nodes or execute pre-configured queries to see how GSD Graph maps and traverses complex codebase knowledge.
Interactive Grounded Knowledge Graph
Milestone 07
Safer auto mode execution and worktree isolation for agentic coding.
How GSD Graph Works
A deterministic 5-stage pipeline turning unstructured files into a rich, queryable knowledge network for developers and AI agents.
Ingest & AST Parse
Scans markdown specs, ADRs, codebases (TypeScript, Python, Rust, Go), and git commit histories without hallucinations.
Entity & Relation Extraction
Identifies components, APIs, milestones, decisions, invariants, and dependencies with exact source file line-spans.
Graph Normalization
Resolves aliases and cross-document references into a unified topological graph (:DEPENDS_ON, :IMPLEMENTS, :VERIFIES).
Local Vector Grounding
Pairs relational graph structure with local fast embeddings for hybrid topological and semantic searches.
Agent Context Synthesis
Feeds precise subgraphs and verified line-level citations into Claude Code, Cursor, Codex, and gsd-pi prompts.
Native MCP Server for AI Coding Agents
Plug GSD Graph directly into Claude Code, Cursor, Windsurf, Copilot, or gsd-pi. Agents can inspect entities, run path traversals, and cite line-level evidence without context blow-up.
graph_query, find_related, and get_citations.{
"mcpServers": {
"gsd-graph": {
"command": "npx",
"args": ["-y", "@opengsd/gsd-graph@latest", "mcp"],
"env": {
"GSD_GRAPH_ROOT": "."
}
}
}
}Why GSD Graph?
How GSD Graph compares to traditional hosted graph databases and raw vector search.
| Feature | GSD Graph (Open GSD) | Hosted Graph DBs (Neo4j, etc.) | Raw Vector Search (Pinecone, etc.) |
|---|---|---|---|
| Local / Offline First | ✓ 100% Local (SQLite-vec) | Requires Server / Cloud | Cloud Hosted API |
| Setup Complexity | ✓ 1-line (`npx @opengsd/gsd-graph`) | Docker, JVM, Cluster Config | API Keys, Billing, Index Setup |
| Multi-Hop Traversal | ✓ Native Topological Query | Supported via Cypher | ❌ No relation awareness |
| Line-Level Citations | ✓ Exact File & Line Spans | Manual schema mapping | Coarse document chunks |
| AI Agent MCP Integration | ✓ Built-in stdio / SSE MCP Server | Custom adapters needed | Custom wrapper needed |
| License & Cost | ✓ Free & MIT Licensed | Enterprise tiers / high cost | Per-query / storage fees |
Build Your First Knowledge Graph in Seconds
Join open-source developers who are making agentic coding grounded, deterministic, and verifiable.