Ziplex

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Turn any local project into a context file an AI can load instantly — instead of reading through hundreds of raw files.

Ziplex walks a project, compresses and structures it with Tree-sitter, summarizes it with an LLM (optional — see Quick start for the no-API-key path), and lets a human correct the result before it ships. The output is aif.json: a small, structured "AI context format" file.

⚠️ Under active development. Interfaces and output format may still change.

Where it helps

• Giving an AI assistant your project's shape once, not every session — paste aif.json into a chat, point an MCP client at it, or open it in the GUI, instead of re-explaining file layout and conventions every time.
• Multi-language projects — a TypeScript frontend, a Python or Java backend, config and docs in between: one pack covers all of it, with cross-file relationships intact.
• Game modding and asset projects that aren't git repos — a Godot scene referencing a GDScript/Lua script by path, a Lua mod with loose asset files: Ziplex tracks those relationships even for files with no Tree-sitter grammar of their own (see Features).
• Onboarding an AI onto a codebase you didn't write — summaries are human-reviewed before they ship, so you're not trusting a raw LLM guess about unfamiliar code.
• Keeping a CI context budget honest — --max-tokens fails a build if the packed payload grows past what a target model can hold.
• Sharing one AI context across a team — aif.json/detail.json are just files; commit them like any other generated artifact (see Team use).

Quick start

pip install ziplex        # or: venv\Scripts\activate && pip install -e . from a clone

Try it right now — no API key, no signup, no network call:

ziplex pack ./your-project/ --auto --no-llm

This runs the full pipeline (Tree-sitter compression, dependency graph, tech-stack detection) and writes a real aif.json — summaries are just a structural listing of each file's own signatures instead of an LLM-written description. See what that looks like on your own project before deciding whether the AI-written version is worth an API key.

Liked it? Add a .env with GEMINI_API_KEY=... (optionally GEMINI_MODEL=... too — see Tech stack), drop --no-llm, and get real AI-written summaries plus inferred coding rules and a project guide:

ziplex pack ./your-project/                        # full pipeline, interactive
ziplex pack ./your-project/ --auto --auto-correct  # fully non-interactive (CI, scripted runs)

--auto (skip interactive file selection) and --auto-correct (skip interactive correction) are independent, so any combination of the two works. Re-running pack on a project you've packed before only re-summarizes files that actually changed (by content hash) — everything else reuses its previous summary instead of another LLM call.

Config file

ziplex init ./your-project/ scaffolds .ziplex.json in the target project (not in Ziplex's own repo) so include/ignore glob patterns don't need retyping on every pack:

// your-project/.ziplex.json
{
  "include": ["src/**/*.py", "*.md"],  // empty = everything not ignored (default)
  "ignore": ["**/*.generated.*"]        // extra patterns beyond DEFAULT_IGNORE/.gitignore
}

--include/--ignore CLI flags add to this file's patterns rather than replacing them. Every subcommand that previews what pack would collect (collect, tree, tokens, search, freshness, select, analyze) reads the same file, so none of them drift out of sync with what a real pack on that project would actually see. Worth committing alongside the project the same way aif.json/detail.json already can (see Team use below) — it documents how that project gets packed.

How it works

Ziplex collects a project's files (skipping build artifacts and anything .gitignored), security-scans them for secrets, and parses the safe ones with Tree-sitter to pull out signatures, imports, and API routes. Function bodies get compressed down to a single marker; an LLM then writes a one-line summary per file plus project-wide coding rules and an AI-facing guide. A human reviews and edits all of that — only low-confidence summaries get flagged, not every file — before the final aif.json (small, loaded up front) and its heavier sibling detail.json (full compressed body, fetched on demand) are saved.

Output format

A pack produces three files, each read differently:

// aif.json — small, loaded up front
{
  "project": {
    "name": "...", "prompt": "...",
    "tech_stack": [{ "manifest": "package.json", "language": "JavaScript/TypeScript", "package_manager": "npm", "dependencies": ["react", "..."], "dependencies_truncated": false }],
    "security_scan": { "flagged": 0, "included_anyway": 0, "excluded": 0 },
    "format_notes": "..."  // fixed legend explaining confidence/⋮---- to a reader with no other Ziplex context
  },
  "rules": ["..."],
  "tokens": { "GPT-4o": { "original": 3100, "compressed": 749, "saved_pct": 75.8 } },
  "files": { "src/App.tsx": { "summary": "...", "confidence": 0.83 } },
  "relationships": { "src/App.tsx": { "internal": ["..."], "external": ["react"] } }
}

// out.detail.json — heavier, fetched only when a file actually needs a closer look
{
  "src/App.tsx": { "compressed": "import React ...\n    ⋮----\nexport default App" }
}

// out.cache.json — internal bookkeeping, not meant for an AI to read; a
// content-hash snapshot of what was packed, for check_freshness to diff
// against later
{
  "src/App.tsx": "3b1c2e...(sha256)"
}

Features

• Multi-language, structure-aware compression — Python, Java, TypeScript, JavaScript, Lua, GDScript, Go, C++, Rust, C#, PHP, Ruby via Tree-sitter, plus dedicated JSON/YAML/Markdown/plain-text compressors, all preserving structure while cutting tokens. Works on any collection of local files with cross-file relationships, not just git repos — game mods and asset projects included.
• Security scanning built in — every file is checked for secrets (secretlint, regex fallback) before it ever enters the pipeline.
• Human-in-the-loop, but it scales — every LLM output (summaries, rules, project guide, dependency tree) is reviewable and editable, or skippable entirely with --auto-correct. Only low-confidence summaries get flagged for review — review time doesn't grow with project size.
• Three ways to consume the result — an MCP server for Claude Code/Cursor/etc., a local GUI for packing and browsing without a terminal, or a Claude Agent Skill export that needs no server at all.
• Cheap to keep current — incremental re-pack only re-summarizes files that actually changed (content hash), retries with backoff on LLM flakiness, and checkpoints a failed run instead of restarting from scratch.
• No API key required, if you want — pack --no-llm skips every LLM call and still produces structural summaries, dependency graphs, and tech-stack detection. Scope any pack with .ziplex.json/--include/--ignore, and guard CI budgets with --max-tokens.

Testing

pip install -e ".[dev]"   # adds pytest on top of the base install
pytest

Covers the deterministic core — compressors, the Tree-sitter extractor, the collector's ignore/binary-file filtering, the dependency-graph operations (build_tree/has_cycle/move_file), and the pure aif-editing API — plus a full pack() run against a network-free MockProvider instead of Gemini, exercising checkpointing, parallel summaries, and token counting end to end without the cost or latency of a real LLM call.

Want to smoke-test pack against a real project without waiting on Gemini? LLM_PROVIDER=mock ziplex pack <project> --auto --auto-correct runs the whole pipeline network-free in under a second.

MCP server

Query an already-packed project directly from Claude Code, Cursor, or any other MCP client — no copy-pasting aif.json into a prompt.

ziplex-mcp                              # run directly (stdio transport)
claude mcp add ziplex -- ziplex-mcp     # register with Claude Code

Read-only and deliberately so: every tool serves an aif.json/detail.json a human already reviewed via correct_aif() — none of them re-pack or re-correct a project on their own, since that would skip the human-in-the-loop step that's the point of Ziplex. get_dependents/get_blast_radius run on the same human-corrected relationships graph pack builds — not a fresh, uncorrected guess.

aif.json/detail.json are snapshots from the last pack run, so they can drift from an actively-changing project. Every tool above except search_project (which always reads files live) trusts that snapshot — call check_freshness first if you suspect it's gone stale, or just pass project_path to get_overview/list_files and let them check for you: a stale pack gets an extra _stale field in the result instead of silently being trusted. It won't fix anything, but it tells you whether a re-pack is warranted before you trust the rest.

GUI

A local, single-user GUI for two situations: packing a project without touching a terminal, and browsing an already-packed project somewhere Claude Code (or MCP generally) isn't available but a browser-based AI chat is.

ziplex-gui                                            # native window (pywebview)
ziplex-gui --aif out.json --project ./your-project/   # prefill the landing page
ziplex-gui --no-window                                # plain browser tab instead

Pack from the GUI — pick a project folder with the native folder picker, check off which files to include (the same safe/dangerous split collect's security scan produces), optionally check "no LLM" (pack --no-llm's GUI equivalent), and watch the pack run in the background. Analysis pauses for review before anything is saved: edit the project name, guide, rules, and per-file summaries (only the low-confidence ones are flagged, same triage the CLI uses). The dependency graph opens as a collapsible whole-tree overview first — click a file's name once you've spotted one worth fixing to drop into an edit view for just that file, linking or unlinking individual edges (a file with more than one real parent keeps its other references intact).

Browse an existing pack — the same overview/files/relationships/detail/search views the MCP server exposes, as web pages instead of MCP tool calls. The Relationships page reuses the same whole-tree-then-edit-one-file flow packing uses, so a relationship noticed after the fact can be fixed without re-running the pipeline. Each page has a Copy button; the intended flow is looking around here and pasting what's useful into a separate AI chat by hand, not the GUI talking to that chat itself.

Binds to 127.0.0.1 only — no --host flag, no way to expose it to a network.

Claude Agent Skill export

A third way to reach a packed project, alongside the MCP server and the GUI — for when Claude Code is available but registering an MCP server isn't (or is more setup than the moment calls for):

ziplex skill result/my-project.json               # writes .claude/skills/my-project/
ziplex skill result/my-project.json -o some/dir    # custom output directory

Generates a Claude Agent Skill — SKILL.md plus references/overview.md/files.md/relationships.md/detail.json — that Claude Code discovers and progressively loads on its own once it sits under .claude/skills/, no server process required. Unlike repomix's equivalent --skill-generate feature, references/files.md never embeds full raw source — it stays to summaries and confidence scores, exactly what aif.json itself already restricts to; the compressed body only ships as references/detail.json. Committing the generated directory works the same way committing aif.json/detail.json does (see Team use below) — it's just files.

Team use

Ziplex packs one person's local snapshot — there's no shared server or live sync. That doesn't rule out team use, though: aif.json/detail.json/cache.json are just files, so a team can commit them to the project's own repo the same way any other generated-but-versioned artifact works.

• Whoever runs pack after a meaningful change commits the refreshed output alongside their code change.
• Everyone else's copy is only as current as the last commit that touched it — check_freshness (or get_overview/list_files with project_path passed, see above) tells them whether their working copy has drifted from what's committed, without re-packing just to find out.
• This is a convention, not a feature Ziplex enforces or coordinates: no merge/conflict resolution, and no defined "who wins" if two people repack independently before either commits. If it does conflict, don't hand-resolve the JSON — see merge-conflicts.md for the recommended fix (clear the conflict, re-pack, review); gitattributes keeps these files collapsed in GitHub's PR diff view.

CI gate (optional): ziplex freshness <project> <name>.cache.json exits non-zero when the committed output has drifted — no LLM calls, no GEMINI_API_KEY, just a hash comparison. Wire it into a PR check (template) to catch a stale, un-re-reviewed aif.json before it merges, without automating pack itself (which costs real LLM calls and skips human review — left as a manual step on purpose).

Tech stack

Python 3.10+ · Tree-sitter (Python/Java/TypeScript/JavaScript/Lua/GDScript/Go/C++/Rust/C#/PHP/Ruby grammars, GDScript via tree-sitter-language-pack) · tiktoken · ruamel.yaml · Gemini API (gemini-flash-latest by default, overridable via GEMINI_MODEL; plain REST via requests) · MCP · Flask · pywebview · secretlint · pathspec

License

MIT