Kai

Semantic infrastructure for code change.

Kai understands what code means — functions, dependencies, behavior impact — not just which lines changed. This semantic graph powers precise CI, context-aware IDEs, and verifiable AI coding agents.

kaicontext.com · Docs · Slack

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Install

# curl
curl -sSL https://get.kaicontext.com | sh

# Homebrew
brew install kaicontext/kai/kai

Quick Start

kai init                      # One-shot setup: graph, MCP, account, remote
kai capture -m "Initial"      # Snapshot your code with a message
kai push                      # Push to kaicontext.com
kai diff                      # Semantic change impact

kai init runs a single, low-friction setup flow:

1. Creates the semantic graph in .kai/ and builds the first capture.
2. Imports git history automatically (for repos with ≤1000 commits) — no prompt.
3. Installs git hooks for auto-capture on commit and auto-push on git push.
4. Installs the Kai MCP server for any detected AI coding tool (Claude Code, Codex). If the kai MCP is already registered, it's left alone; otherwise it's added automatically — no prompt.
5. Signs you up for kaicontext.com in-place: asks for your email, emails you a login link, you paste the token back, and Kai creates a personal org named after you plus a repo for the current directory. Your first push goes out at the end of init.

Every step runs by default. Press Ctrl+C to skip the account step if you'd rather stay local; everything else is automatic.

For full command reference, see docs/cli-reference.md.

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MCP Server

Kai ships an MCP server that gives AI coding assistants access to call graphs, dependency maps, impact analysis, and test coverage.

# Claude Code
claude mcp add kai -- kai mcp serve

# Or without installing kai (npx downloads it automatically)
claude mcp add kai -- npx -y kai-mcp

No setup required — the server lazily initializes the semantic graph on first use.

12 tools: kai_status, kai_symbols, kai_files, kai_diff, kai_impact, kai_callers, kai_callees, kai_context, kai_dependencies, kai_dependents, kai_tests, kai_refresh.

See docs/mcp.md for Cursor setup, tool reference, and troubleshooting.

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Code Reviews

Kai reviews are anchored to semantic changesets, not line diffs.

kai review open --title "Add auth middleware"   # Create a review
kai push                                         # Push to kaicontext.com
kai fetch --review abc123                        # Sync comments from web
kai review comments abc123                       # View inline comments locally

On the web, reviews show semantic diffs (what functions changed, not just which lines), inline commenting, and one-click merge that updates snap.main.

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CI Integration

Kai CI runs workflows defined in .kailab/workflows/ with semantic checkout, parallel jobs, and 30-minute default timeouts.

kai ci runs                   # List CI runs
kai ci logs 42                # View logs for run #42
kai ci cancel 42              # Cancel a run
kai capture -m "Fix bug"      # Message shows as CI run headline

Email notifications on pipeline completion are sent to the snapshot author via Postmark.

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What Kai Builds

For every capture, Kai constructs a queryable semantic model:

Layer	What It Captures
Functions & methods	Signatures, bodies, call graphs
Dependencies	Module relationships, imports, data flow
Behavior changes	What actually changed in meaning, not just text
Test coverage	Which tests cover which source files (static + transitive)

This graph is immutable, content-addressed, and designed for machine reasoning.

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Use Cases

Selective CI

Kai determines which tests actually need to run based on behavioral impact, not file diffs. Result: 80% CI time reduction for early users.

AI Code Context

12 MCP tools give AI assistants structured access to your codebase's dependency graph, call graph, impact analysis, and test coverage.

Code Reviews

Semantic diff shows what changed (function added, condition modified, API changed) instead of raw line diffs. Inline comments anchored to symbols, not lines.

Verified AI Agents

Agent proposes edit → Kai validates impact → agent executes with proof, not generation with hope.

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Language Support

Kai uses tree-sitter for parsing and builds semantic graphs for 9 languages. Each language is validated with end-to-end tests against real open-source projects:

Language	Symbols	Callers/Callees	Dependencies	Tests	Impact	E2E Fixtures
Go	functions, methods, interfaces, structs	cross-package via import aliases	Go package resolution	same-dir _test.go + transitive	via dependency graph	chi, lo
Rust	functions, structs, enums, traits, impl methods, macros	cross-file via exports	crate::, super::, self::, mod, wildcards	filename pattern matching for integration tests	via dependency graph	just, miniserve
TypeScript/JavaScript	functions, classes, methods, variables	via imports	relative + workspace resolution	*.test.ts, __tests__/ patterns	via dependency graph	—
Python	functions, classes, methods	via imports	dotted module resolution	test_*.py, *_test.py patterns	via dependency graph	—
Ruby	methods, classes, modules	via exports	require, require_relative, Zeitwerk autoload	*_spec.rb, *_test.rb patterns	via dependency graph	—
SQL	—	—	—	—	—	—
PHP	functions, classes, methods	—	—	—	—	—
C#	functions, classes, methods	—	—	—	—	—

92 E2E tests across Go, Rust, and push completeness, all passing. Run them with:

cd kai-e2e && ./scripts/run-tests.sh

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Architecture

Kai is fully open source under Apache 2.0: core engine, CLI, and server. Kai Cloud is the hosted version — same code, managed infrastructure.

kai capture → local semantic graph (SQLite)
kai push    → kaicontext.com (Postgres + GCS)
                ├── File viewer with search, language breakdown
                ├── CI with SSE live updates
                ├── Code reviews with semantic diffs
                └── Email notifications (Postmark)

See What's Open Source vs. Kai Cloud.

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License

See LICENSE.

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Community & Contributing

• Slack
• Contributing guidelines