Contextual Labs
Contextual Labs — local-first AI context engine with semantic search, temporal recall, and on-device indexing.
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What is Contextual Labs?
Contextual Labs makes Contextual, a local-first AI context engine that provides semantic search, temporal code analysis, and impact tracing for AI coding agents. It runs entirely on-device with local embeddings and LanceDB, integrating via MCP with Cursor, Claude Code, VS Code, and other editors to help AI agents understand code history and make contextual decisions.
Contextual Labs pricing
Pricing model: Freemium
Contextual Labs pros
- Zero-cloud architecture — all embeddings, indexing, and graph processing run on-device with zero egress; no code leaves your machine
- Temporal semantic search — remembers why decisions were made with git blame, commit history, PR context, and architectural decision records integrated
- Native MCP integration — plugs directly into Cursor, Claude Desktop, VS Code, and AI agents without custom glue
- 22 built-in tools — impact analysis, coupling detection, decision tracking, and blame-enriched history across five tool classes
- Lightweight and reversible — ~120MB resident, 5 minutes to index 50k LOC, single binary, rm -rf to uninstall
Contextual Labs cons
- Requires Python 3.11+ environment (uvx/pipx); limited platform support for Windows (WSL2 only, not native)
- Still in beta (v1.0.0) with potential breaking changes and incomplete feature parity
- Proprietary license — not open source; pricing model not yet disclosed at launch
- Requires initial indexing and filesystem watcher overhead; may not support all languages equally despite agnosticism claims
Frequently asked questions about Contextual Labs
Does Contextual send my code to a server?
No. Contextual is zero-cloud. Embeddings, index, and graph live in ~/.contextual. Nothing is uploaded, nothing is logged, nothing leaves the device.
How does Contextual stay in sync with my code?
A filesystem watcher keeps the index and graph current. Rename a function and recall updates automatically. Drop a branch and the timeline forks.
How fast are search queries?
Median recall latency is 93.85ms with answers assembled entirely on-device and 0 tokens sent to any server.
What if I want to uninstall it?
One folder, one binary. rm -rf ~/.contextual and it's like it never happened — fully reversible by design.