Aidex

AiDex

[npm version] [MIT License] [Node.js 20+] [MCP Server] [GitHub Discussions]

The persistent brain for AI coding agents.

AiDex is an MCP server that gives AI coding assistants a memory, semantic search, and live telemetry — local-first, model-agnostic. Works with any MCP-compatible AI assistant: Claude Code, Claude Desktop, Cursor, Windsurf, Gemini CLI, VS Code Copilot, and more.

Three Pillars

🧠 Memory — Tasks, notes, and session-notes survive every chat. Auto-logged history, scheduled tasks, cross-session continuity. Your AI knows tomorrow what mattered today.

🔍 Search — Three modes: exact (identifier), semantic (concept), hybrid (RRF fusion of both). Embeds code, docs, and workspace items into one ranking. Cross-project — every repo in one query. Optional LLM layer translates non-English queries and reranks results.

🌐 Telemetry — LogHub receives live logs from any app via HTTP (no SDK). The AI watches what your code actually does, not just what it says. Live-streamed in the Viewer.

What's Inside — 33 Tools in One Server

14 languages — C#, TypeScript, JavaScript, Rust, Python, C, C++, Java, Go, PHP, Ruby, HCL/Terraform, Kotlin, Swift — plus Astro frontmatter

# Find where "PlayerHealth" is defined — 1 call, ~50 tokensaidex_query({ term: "PlayerHealth" })→ Engine.cs:45, Player.cs:23, UI.cs:156
# All methods in a file — without reading the whole fileaidex_signature({ file: "src/Engine.cs" })→ class GameEngine { Update(), Render(), LoadScene(), ... }
# What changed in the last 2 hours?aidex_query({ term: "render", modified_since: "2h" })
# Search across ALL your projects at onceaidex_global_query({ term: "TransparentWindow", mode: "contains" })→ Found in: LibWebAppGpu (3 hits), DebugViewer (1 hit)
# Leave a note for your next sessionaidex_note({ path: ".", note: "Test the parser fix after restart" })
# Create a task while workingaidex_task({ path: ".", action: "create", title: "Fix edge case in parser", priority: 1, tags: "bug" })

Table of Contents

• What's Inside
• Semantic Search & LLM Layer 🆕
• The Problem
• The Solution
• Why Not Just Grep?
• How It Works
• Features
• Supported Languages
• Quick Start
• Available Tools
• Time-based Filtering
• Project Structure
• Session Notes
• Task Backlog
• Global Search
• AI Guidelines
• Log Hub
• Debug Dashboard
• Screenshots — LLM-Optimized
• Interactive Viewer
• CLI Usage
• Performance
• Technology
• Contributing
• License

Semantic Search & LLM Layer

v2.0 added semantic search via locally-run embeddings — your AI can find a function even when it doesn't know the exact identifier.

Three modes — pick the right tool for the question

What gets embedded

• Code — every method and type, three-tier chunking (signature + doc-comment + weighted identifier bag)
• Docs — Markdown sections (README, CHANGELOG, docs/, plan files), split at heading boundaries
• Workspace — tasks, task logs, session notes, archived note history

One ranking, all kinds. A query like "how to write logs from external programs" surfaces the README's ## Log Hub section first, then the log method in commands/log.ts, then any related task.

Setup

// Enable embeddings on a project (one-time, ~30s for AiDex itself, cached afterwards)aidex_init({ path: ".", embeddings: true })
// Searchaidex_search({ query: "how do we batch requests to the LLM", path: "." })aidex_search({ query: "retry with backoff", scope: "all" })  // across every embedded project

Or use the Settings tab in the Viewer (aidex_settings({ path: ".", open: true })) — toggles for embeddings, LLM provider, model, and the privacy switch.

Optional LLM layer

When an Anthropic / OpenAI / OpenRouter / Ollama / HuggingFace API key is configured, AiDex can:

• Translate non-English queries → "wie speichere ich Logs lokal" finds the right code
• Expand vague queries into 2-4 concrete subqueries (RRF-merged)
• Rerank top-N retrieval candidates

Privacy switch llm_send_code defaults to off — only your literal query and metadata (paths, names, anchors) are sent. Code bodies stay local. Per-project, easy to verify in Settings.

Local-first: works fully offline with pure embeddings. The LLM layer is opt-in, never required.

The Problem

Every time your AI assistant searches for code, it:

• Greps through thousands of files → hundreds of results flood the context
• Reads file after file to understand the structure → more context consumed
• Forgets everything when the session ends → repeat from scratch

A single "Where is X defined?" question can eat 2,000+ tokens. Do that 10 times and you've burned half your context on navigation alone.

The Solution

Index once, query forever:

# Before: grep flooding your contextAI: grep "PlayerHealth" → 200 hits in 40 filesAI: read File1.cs, File2.cs, File3.cs...→ 2000+ tokens consumed, 5+ tool calls
# After: precise results, minimal contextAI: aidex_query({ term: "PlayerHealth" })→ Engine.cs:45, Player.cs:23, UI.cs:156→ ~50 tokens, 1 tool call

Result: 50-80% less context used for code navigation.

Why Not Just Grep?

The real cost of grep: Every grep result includes surrounding context. Search for User in a large project and you'll get hundreds of hits - comments, strings, partial matches. Your AI reads through all of them, burning context tokens on noise.

AiDex indexes identifiers: It uses Tree-sitter to actually parse your code. When you search for User, you get the class definition, the method parameters, the variable declarations - not every comment that mentions "user".

How It Works

1. Index your project once (~1 second per 1000 files)

   aidex_init({ path: "/path/to/project" })

2. AI searches the index instead of grepping

   aidex_query({ term: "Calculate", mode: "starts_with" })→ All functions starting with "Calculate" + exact line numbers
   aidex_query({ term: "Player", modified_since: "2h" })→ Only matches changed in the last 2 hours

3. Get file overviews without reading entire files

   aidex_signature({ file: "src/Engine.cs" })→ All classes, methods, and their signatures

The index lives in .aidex/index.db (SQLite) - fast, portable, no external dependencies.

Features

• Tree-sitter Parsing: Real code parsing, not regex — indexes identifiers, ignores keywords and noise
• ~50 Tokens per Search: vs 2000+ with grep — your AI keeps its context for actual work
• Persistent Index: Survives between sessions — no re-scanning, no re-reading
• Incremental Updates: Re-index single files after changes, not the whole project
• Time-based Filtering: Find what changed in the last hour, day, or week
• Auto-Cleanup: Excluded files (e.g., build outputs) are automatically removed from index
• Zero Dependencies: SQLite with WAL mode — single file, fast, portable

Supported Languages

Quick Start

Prerequisites

• Node.js ≥ 20 (check with node --version)
  • macOS: brew install node or nvm install 20 && nvm use 20
  • Linux: use your package manager or nvm
  • Windows: nodejs.org
  • If you use nvm, the repo ships a .nvmrc — nvm use picks the right version automatically.

1. Install

npm install -g aidex-mcp

That's it. Setup runs automatically after install — it detects your installed AI clients (Claude Code, Claude Desktop, Cursor, Windsurf, Gemini CLI, VS Code Copilot) and registers AiDex as an MCP server. It also adds usage instructions to your AI's config (~/.claude/CLAUDE.md, ~/.gemini/GEMINI.md).

To re-run setup manually: aidex setup | To unregister: aidex unsetup | To skip auto-setup: AIDEX_NO_SETUP=1 npm install -g aidex-mcp

2. Or register manually with your AI assistant

For Claude Code (~/.claude/settings.json or ~/.claude.json):

{  "mcpServers": {    "aidex": {      "type": "stdio",      "command": "aidex",      "env": {}    }  }}

For Claude Desktop (%APPDATA%/Claude/claude_desktop_config.json on Windows):

{  "mcpServers": {    "aidex": {      "command": "aidex"    }  }}

Note: Both aidex and aidex-mcp work as command names.

Important: The server name in your config determines the MCP tool prefix. Use "aidex" as shown above — this gives you tool names like aidex_query, aidex_signature, etc. Using a different name (e.g., "codegraph") would change the prefix accordingly.

For Gemini CLI (~/.gemini/settings.json):

{  "mcpServers": {    "aidex": {      "command": "aidex"    }  }}

For VS Code Copilot (run MCP: Open User Configuration in Command Palette):

{  "servers": {    "aidex": {      "type": "stdio",      "command": "aidex"    }  }}

For other MCP clients: See your client's documentation for MCP server configuration.

3. Make your AI actually use it

Add to your AI's instructions (e.g., ~/.claude/CLAUDE.md for Claude Code, or the equivalent for your AI client). This tells the AI when and how to use AiDex instead of grepping:

## AiDex - Persistent Code Index (MCP Server)
AiDex provides fast, precise code search through a pre-built index.**Always prefer AiDex over Grep/Glob for code searches.**
### REQUIRED: Before using Grep/Glob/Read for code searches

Do I want to search code? ├── .aidex/ exists → STOP! Use AiDex instead ├── .aidex/ missing → run aidex_init (don't ask), THEN use AiDex └── Config/Logs/Text → Grep/Read is fine

**NEVER do this when .aidex/ exists:**- ❌ `Grep pattern="functionName"` → ✅ `aidex_query term="functionName"`- ❌ `Grep pattern="class.*Name"` → ✅ `aidex_query term="Name" mode="contains"`- ❌ `Read file.cs` to see methods → ✅ `aidex_signature file="file.cs"`- ❌ `Glob pattern="**/*.cs"` + Read → ✅ `aidex_signatures pattern="**/*.cs"`
### Session-Start Rule (REQUIRED — every session, no exceptions)
1. Call `aidex_session({ path: "<project>" })` — detects external changes, auto-reindexes2. If `.aidex/` does NOT exist → run `aidex_init` automatically (don't ask)3. If a session note exists → **show it to the user** before continuing4. **Before ending a session:** always leave a note about what to do next
### Question → Right Tool
| Question | Tool ||----------|------|| "Where is X defined?" | `aidex_query term="X"` || "Find anything containing X" | `aidex_query term="X" mode="contains"` || "All functions starting with X" | `aidex_query term="X" mode="starts_with"` || "What methods does file Y have?" | `aidex_signature file="Y"` || "Explore all files in src/" | `aidex_signatures pattern="src/**"` || "Project overview" | `aidex_summary` + `aidex_tree` || "What changed recently?" | `aidex_query term="X" modified_since="2h"` || "What files changed today?" | `aidex_files path="." modified_since="8h"` || "Have I ever written X?" | `aidex_global_query term="X" mode="contains"` || "Which project has class Y?" | `aidex_global_signatures term="Y" kind="class"` || "All indexed projects?" | `aidex_global_status` |
### Search Modes
- **`exact`** (default): Finds only the exact identifier — `log` won't match `catalog`- **`contains`**: Finds identifiers containing the term — `render` matches `preRenderSetup`- **`starts_with`**: Finds identifiers starting with the term — `Update` matches `UpdatePlayer`, `UpdateUI`
### All Tools (30)
| Category | Tools | Purpose ||----------|-------|---------|| Search & Index | `aidex_init`, `aidex_query`, `aidex_update`, `aidex_remove`, `aidex_status` | Index project, search identifiers (exact/contains/starts_with), time filter || Signatures | `aidex_signature`, `aidex_signatures` | Get classes + methods without reading files || Overview | `aidex_summary`, `aidex_tree`, `aidex_describe`, `aidex_files` | Entry points, file tree, file listing by type || Cross-Project | `aidex_link`, `aidex_unlink`, `aidex_links`, `aidex_scan` | Link dependencies, discover projects || Global Search | `aidex_global_init`, `aidex_global_query`, `aidex_global_signatures`, `aidex_global_status`, `aidex_global_refresh` | Search across ALL projects || Guidelines | `aidex_global_guideline` | Persistent AI instructions & conventions (key-value, global) || Sessions | `aidex_session`, `aidex_note` | Track sessions, leave notes (with searchable history) || Tasks | `aidex_task`, `aidex_tasks` | Built-in backlog with priorities, tags, summaries, auto-logged history, scheduled/recurring tasks || Log Hub | `aidex_log` | Universal log receiver — any program sends logs via HTTP, AI queries them, live in Viewer || Screenshots | `aidex_screenshot`, `aidex_windows` | Screen capture with LLM optimization (scale + color reduction, no index needed) || Viewer | `aidex_viewer` | Interactive browser UI with file tree, signatures, tasks, and live logs |
**14 languages:** C#, TypeScript, JavaScript, Rust, Python, C, C++, Java, Go, PHP, Ruby, HCL/Terraform, Kotlin, Swift — plus Astro frontmatter
### Session Notes
Leave notes for the next session — they persist in the database:

aidex_note({ path: ".", note: "Test the fix after restart" }) # Write aidex_note({ path: ".", note: "Also check edge cases", append: true }) # Append aidex_note({ path: "." }) # Read aidex_note({ path: ".", search: "parser" }) # Search history aidex_note({ path: ".", clear: true }) # Clear

- **Before ending a session:** automatically leave a note about next steps- **User says "remember for next session: ..."** → write it immediately
### Task Backlog
Track TODOs, bugs, and features right next to your code index:

aidex_task({ path: ".", action: "create", title: "Fix bug", priority: 1, tags: "bug" }) aidex_task({ path: ".", action: "update", id: 1, status: "done" }) aidex_task({ path: ".", action: "log", id: 1, note: "Root cause found" }) aidex_tasks({ path: ".", status: "active" })

Scheduled & recurring tasks

aidex_task({ path: ".", action: "create", title: "Check PR status", due: "3d", interval: "3d", task_action: "gh pr list" })

Priority: 1=high, 2=medium, 3=low | Status: `backlog → active → done | cancelled`
### Global Search (across all projects)

aidex_global_init({ path: "/path/to/all/repos" }) # Scan & register aidex_global_init({ path: "...", index_unindexed: true }) # + auto-index small projects aidex_global_query({ term: "TransparentWindow", mode: "contains" }) # Search everywhere aidex_global_signatures({ term: "Render", kind: "method" }) # Find methods everywhere aidex_global_status({ sort: "recent" }) # List all projects

### Screenshots

aidex_screenshot() # Full screen aidex_screenshot({ mode: "active_window" }) # Active window aidex_screenshot({ mode: "window", window_title: "VS Code" }) # Specific window aidex_screenshot({ scale: 0.5, colors: 2 }) # B&W, half size (ideal for LLM) aidex_screenshot({ colors: 16 }) # 16 colors (UI readable) aidex_windows({ filter: "chrome" }) # Find window titles

No index needed. Returns file path → use `Read` to view immediately.
**LLM optimization strategy:** Always start with aggressive settings, then retry if unreadable:1. First try: `scale: 0.5, colors: 2` (B&W, half size — smallest possible)2. If unreadable: retry with `colors: 16` (adds shading for UI elements)3. If still unclear: `scale: 0.75` or omit `colors` for full quality4. **Remember** what works for each window/app during the session — don't retry every time.

4. Index your project

Ask your AI: "Index this project with AiDex"

Or manually in the AI chat:

aidex_init({ path: "/path/to/your/project" })

Available Tools

Time-based Filtering

Track what changed recently with modified_since and modified_before:

aidex_query({ term: "render", modified_since: "2h" })   # Last 2 hoursaidex_query({ term: "User", modified_since: "1d" })     # Last dayaidex_query({ term: "API", modified_since: "1w" })      # Last week

Supported formats:

• Relative: 30m (minutes), 2h (hours), 1d (days), 1w (weeks)
• ISO date: 2026-01-27 or 2026-01-27T14:30:00

Perfect for questions like "What did I change in the last hour?"

Project Structure

AiDex indexes ALL files in your project (not just code), letting you query the structure:

aidex_files({ path: ".", type: "config" })  # All config filesaidex_files({ path: ".", type: "test" })    # All test filesaidex_files({ path: ".", pattern: "**/*.md" })  # All markdown filesaidex_files({ path: ".", modified_since: "30m" })  # Changed this session

File types: code, config, doc, asset, test, other, dir

Use modified_since to find files changed in this session - perfect for "What did I edit?"

Session Notes

Leave reminders for the next session - no more losing context between chats:

aidex_note({ path: ".", note: "Test the glob fix after restart" })  # Writeaidex_note({ path: ".", note: "Also check edge cases", append: true })  # Appendaidex_note({ path: "." })                                              # Readaidex_note({ path: ".", clear: true })                                 # Clear

Note History (v1.10): Old notes are automatically archived when overwritten or cleared. Browse and search past notes:

aidex_note({ path: ".", history: true })                    # Browse archived notes (shows summaries)aidex_note({ path: ".", search: "parser" })                 # Search note history (searches summaries too)aidex_note({ path: ".", history: true, limit: 5 })          # Last 5 archived notes

Note Summaries (v1.15): Provide a summary when writing/clearing a note — the archived note gets this one-sentence description. History then shows summaries instead of truncated text:

aidex_note({ path: ".", note: "New focus", summary: "Previous session: finished parser refactoring" })

Use cases:

• Before ending a session: "Remember to test X next time"
• AI auto-reminder: Save what to verify after a restart
• Handover notes: Context for the next session without editing config files
• Search past sessions: "What did we do about the parser?"

Notes are stored in the SQLite database (.aidex/index.db) and persist indefinitely.

Task Backlog

Keep your project tasks right next to your code index - no Jira, no Trello, no context switching:

aidex_task({ path: ".", action: "create", title: "Fix parser bug", priority: 1, tags: "bug", summary: "Parser crashes on nested generics in C#" })aidex_task({ path: ".", action: "update", id: 1, status: "done" })aidex_task({ path: ".", action: "log", id: 1, note: "Root cause: unbounded buffer" })aidex_tasks({ path: ".", status: "active" })

Scheduled & Recurring Tasks

Tasks can have due dates and repeat intervals. Overdue tasks are reported at every session start across ALL projects:

# One-shot: remind in 3 daysaidex_task({ path: ".", action: "create", title: "Review PR", due: "3d", task_action: "Check if PR was submitted" })
# Recurring: check every weekaidex_task({ path: ".", action: "create", title: "Check dependencies", due: "1w", interval: "1w", task_action: "npm outdated" })
# Auto-execute: runs the action automatically when dueaidex_task({ path: ".", action: "create", title: "Refresh stats", due: "1d", interval: "1d", auto_go: true })

Due formats: Relative ("30m", "2h", "3d", "1w") or ISO date ("2026-04-10")

At every aidex_session call, the Task Scheduler checks ~/.aidex/global.db for due tasks across all projects — even if you're working on a different project. Recurring tasks automatically advance their due date after each trigger.

Features:

• Summaries: One-sentence table-of-contents per task — scan the backlog without reading full details
• Priorities: 🔴 high, 🟡 medium, ⚪ low
• Statuses: backlog → active → done | cancelled
• Tags: Categorize tasks (bug, feature, docs, etc.)
• History log: Every status change is auto-logged, plus manual notes
• Scheduling: Due dates, recurring intervals, actions, auto-execute across all projects
• Viewer integration: Tasks tab in the browser viewer with live updates
• Persistent: Tasks survive between sessions, stored in .aidex/index.db

Your AI assistant can create tasks while working ("found a bug in the parser, add it to the backlog"), track progress, and pick up where you left off next session.

Global Search

Search across ALL your indexed projects at once. Perfect for "Have I ever written a transparent window?" or "Where did I use that algorithm?"

Setup

aidex_global_init({ path: "Q:/develop" })                              # Scan & registeraidex_global_init({ path: "Q:/develop", exclude: ["llama.cpp"] })      # Skip external reposaidex_global_init({ path: "Q:/develop", index_unindexed: true })       # Auto-index all found projectsaidex_global_init({ path: "Q:/develop", index_unindexed: true, show_progress: true })  # With browser progress UI

This scans your project directory, registers all AiDex-indexed projects in a global database (~/.aidex/global.db), and reports any unindexed projects it finds by detecting project markers (.csproj, package.json, Cargo.toml, etc.).

With index_unindexed: true, it also auto-indexes all discovered projects with ≤500 code files. Larger projects are listed separately for user decision. Add show_progress: true to open a live progress UI in your browser (http://localhost:3334).

Search

aidex_global_query({ term: "TransparentWindow" })                      # Exact matchaidex_global_query({ term: "transparent", mode: "contains" })          # Fuzzy searchaidex_global_signatures({ term: "Render", kind: "method" })            # Find methodsaidex_global_signatures({ term: "Player", kind: "class" })             # Find classes

How it works

• Uses SQLite ATTACH DATABASE to query project databases directly — no data copying
• Results are cached in memory (5-minute TTL) for fast repeated queries
• Projects are batched (8 at a time) to respect SQLite's attachment limit
• Each project keeps its own .aidex/index.db as the single source of truth
• Auto-deduplication: Parent projects that contain sub-projects are automatically skipped (e.g., MyApp/ is removed when MyApp/Frontend/ and MyApp/Backend/ exist as separate indexed projects)

Management

aidex_global_status()                                                  # List all projectsaidex_global_status({ sort: "recent" })                                # Most recently indexed firstaidex_global_refresh()                                                 # Update stats, remove stale

AI Guidelines

Store persistent coding conventions, review checklists, and AI instructions in a single place — shared across all projects.

aidex_global_guideline({ action: "set", key: "review", value: "Always check: error handling, null safety, no hardcoded strings" })aidex_global_guideline({ action: "set", key: "style", value: "Use PascalCase for classes, camelCase for methods, 4-space indent" })aidex_global_guideline({ action: "get", key: "review" })               # Retrieve a guidelineaidex_global_guideline({ action: "list" })                             # Show all guidelinesaidex_global_guideline({ action: "list", filter: "code" })             # Filter by nameaidex_global_guideline({ action: "delete", key: "old-rule" })          # Remove a guideline

Use cases:

• Code review checklist: Tell your AI exactly what to look for every time
• Coding conventions: Store team style rules once, reference them in any project
• Release checklist: Step-by-step process for shipping
• Project-agnostic instructions: No more pasting the same context into every session

Guidelines are stored in ~/.aidex/global.db — available across all your projects without aidex_init. Ask your AI: "Load the review guideline and apply it to this file."

Log Hub — Universal Logging

Turn any program into a log source for your AI assistant. Your app sends logs via HTTP POST, the AI queries them via MCP, and you see them live in the Viewer — zero dependencies, zero setup in your code.

How it works

Your Program ──HTTP POST──→ AiDex Log Hub (port 3335) ──→ Ring Buffer                                        │                      │                                        │ WebSocket             │ MCP query                                        ↓                      ↓                                   Viewer (Logs tab)      AI Assistant                                   (you see live)       (queries & analyzes)

Quick start

1. AI starts the Log Hub: aidex_log({ action: "init" })
2. AI opens the Viewer: aidex_viewer({ path: "." }) — Logs tab shows live stream
3. Add one line to your program:

// C#await new HttpClient().PostAsJsonAsync("http://localhost:3335/log",    new { level = "info", source = "MyApp", message = "Player spawned", data = new { x = 10, y = 20 } });

# Pythonrequests.post("http://localhost:3335/log", json={"level": "info", "source": "MyApp", "message": "Done"})

// JavaScriptfetch("http://localhost:3335/log", {    method: "POST", headers: {"Content-Type": "application/json"},    body: JSON.stringify({level: "info", source: "MyApp", message: "Started"})});

# PowerShellInvoke-RestMethod -Uri http://localhost:3335/log -Method POST -ContentType "application/json" -Body '{"level":"info","source":"Script","message":"Done"}'

HTTP API

Fields: level (debug/info/warn/error), source (app name), message (text, required), data (optional JSON), timestamp (optional, ms)

Features

• Ring Buffer: Fixed-size in-memory FIFO (default 10,000 entries) — oldest entries overwritten
• Zero-cost: No server, no buffer, no resources until init is called
• Persistence: Optional SQLite storage with 7-day auto-cleanup (persist: true)
• Consume pattern: query with consume: true removes returned entries — ideal for polling
• Viewer integration: Logs tab with WebSocket live-stream, level/source/text filters, auto-scroll
• Fire & forget: Just POST and go — if the server isn't running, the POST silently fails

Control API — let the AI drive your app

Logs and dashboard widgets flow app → AI. The Control API is the return channel: AI → app. It turns the Log Hub into a tiny, zero-dependency command bus — so an AI assistant can drive any running program without you writing a server.

The AI sets a command; your app polls for it, runs it, and posts the result back:

AI ──control_set {id,cmd}──→  Hub  ←──GET /control──  Your App (polls ~1s)AI ←──control_get──── result ─ Hub  ←──POST /control── runs it, posts result + ack

• control_set { id, value } — the AI (or a Viewer slider/switch) sets a control slot.
• GET /control — your app reads all current control values.
• POST /control — your app writes back results / acknowledgements.
• POST /control/press { id } — registers one press of a button control. The hub owns the counter, so presses from several open dashboards add up instead of overwriting each other.
• control_get — the AI reads what the app reported.
• POST /control/subscribe (optional) — push instead of polling, see below.

Push instead of poll. If your app runs its own HTTP server, it can subscribe once with { "port": 8080 } (the hub calls back the sender's address, path defaults to /control) or a full { "url": "http://192.168.1.50:8080/control" }, optionally limited to { "ids": [...] }. From then on every change is POSTed to that URL right away, as the same flat { id: value } map GET /control returns. No idle requests, no latency until the next poll. The hub never blocks on your app (1.5 s timeout, one request in flight, changes in between are merged so the latest value always arrives last), only calls private-network IP addresses, and drops the subscription after 3 failed deliveries — re-subscribing is idempotent, do it whenever you like. POST /control/unsubscribe { url } removes it. Push is an addition, not a replacement: keep a slow poll (~30 s) as a safety net; button counters make a missed push harmless.

A button value is a press counter, not a flag — your app polls at its own pace, so compare against the last count you saw rather than testing for "pressed". Any backwards jump means the hub restarted or the panel was cleared: adopt the value, don't read it as a million presses.

Two slots by convention give you full request/response: a *_cmd slot the AI writes, a *_result slot the app writes, and an *_ack counter so each command runs exactly once (bump the command id every time; the app skips any id it has already handled).

That's the whole protocol. A client needs nothing but an HTTP library you already have.

Real example — an AI controlling Autodesk Fusion 360

A ~30-line Fusion 360 add-in (urllib only, no SDK) polls GET /control, executes the command on Fusion's main thread, and posts the result back. With nothing else, an AI assistant drove Fusion to parametrically design a complete 3D enclosure — sketches, extrusions, screw-boss domes with heat-set inserts, USB-C cut-outs, reset/button holes — verifying every step by reading back the actual face geometry.

The pattern is universal: anything that can POST and GET — Blender, a CNC controller, a game, a home-automation hub — becomes AI-steerable with a few lines and no bespoke server. Two safety rules carry over from that build:

• Single-thread GUI APIs: the poll loop must never touch the app API directly. Fire an event and run the command on the main thread (the official Fusion pattern; the same holds for any non-thread-safe UI/COM API).
• Idempotency: track the last handled id and ack it — polling means you'll see the same command repeatedly, so skip what you've already done.

Debug Dashboard

The scrolling log stream is great for what happened when — but useless for fast, repeating values (audio levels, buffer fill, FPS, sensor readings). The Debug Dashboard is the opposite: a fixed-slot panel where each value has a permanent spot and overwrites in place instead of scrolling away. Live in the Viewer's Live tab, styled like a hardware monitor (MSI Afterburner / HWiNFO).

It rides on the same Log Hub server — no extra setup. Your program sends widget updates via HTTP POST; sending the same id again updates that widget.

Widget types

Send a widget

# A single widget — id is the fixed slot, type is required on first sendcurl -X POST http://localhost:3335/panel -H "Content-Type: application/json" \  -d '{"id":"mic","type":"plot","value":0.73,"group":"Audio","label":"Mic Level","unit":"dB"}'
# A gauge with threshold zones (green < warn < yellow < crit < red)curl -X POST http://localhost:3335/panel -H "Content-Type: application/json" \  -d '{"id":"gpu_temp","type":"gauge","value":67,"min":0,"max":100,"warn":75,"crit":90,"group":"Hardware"}'

Fields: id (required), type (label/progress/gauge/plot/slider/number/toggle/button, required on first send), value (number, status string, or number array for a full plot frame), group, label, unit, min, max, warn, crit, color, order. Endpoints: POST /panel (one), POST /panels (batch), POST /panel/clear ({id} for one, empty for all).

Lifecycle

• The server keeps the last state per id, so a freshly-opened or reloaded Viewer shows the whole dashboard immediately.
• Cards with no update for ~3 s grey out as "stale".
• Clear is a full reset: it empties the store. A source only reappears if it sends widgets with their type again (plain value-only updates to a cleared id are ignored).
• Backpressure-guarded — a slow browser can't make the server's send-queue grow without bound.

Try it — the built-in demo

A ready-to-run showcase animates all widget types (audio waveform, GPU gauges drifting through their zones, a signal generator cycling sine → sawtooth → triangle → square, latency spikes):

# 1. Start the Log Hub + Viewer from your AI assistant:#      aidex_log({ action: "init" })#      aidex_viewer({ path: "." })       → click the Live tab# 2. Run the demo (from the AiDex repo root):node scripts/demo-dashboard.mjs           # endless loop, Ctrl+C to stop (clears on exit)

Or use the ▷ Demo button on the Live tab — it copies the run command to your clipboard; paste it into a terminal. (The browser can't spawn a process itself.) It sits in the toolbar even while the dashboard is still empty, since it's how you get your first widgets. scripts/demo-dashboard.ps1 is a one-command launcher that checks the Log Hub first.

Running it twice starts two instances that fight over the same widgets (visible flicker) — stop the old one (Ctrl+C) before starting another.

Screenshots — LLM-Optimized

Take screenshots and reduce them up to 95% for LLM context. A typical screenshot goes from ~100 KB to ~5 KB — that's thousands of tokens saved per image.

Why this matters

Most screenshots in AI context are for reading text — error messages, logs, UI labels. You don't need 16 million colors for that.

Usage

aidex_screenshot()                                             # Full screen (full quality)aidex_screenshot({ mode: "active_window" })                    # Active windowaidex_screenshot({ mode: "window", window_title: "VS Code" }) # Specific windowaidex_screenshot({ scale: 0.5, colors: 2 })                   # B&W, half size (best for text)aidex_screenshot({ scale: 0.5, colors: 16 })                  # 16 colors (UI readable)aidex_screenshot({ colors: 256 })                              # 256 colors (good quality)aidex_screenshot({ mode: "region" })                           # Interactive selectionaidex_screenshot({ mode: "rect", x: 100, y: 200, width: 800, height: 600 })  # Coordinatesaidex_windows({ filter: "chrome" })                            # Find window titles

Optimization parameters

Recommended strategy for AI assistants

The tool description tells LLMs to optimize automatically:

1. Start aggressive: scale: 0.5, colors: 2 (smallest possible)
2. If unreadable: retry with colors: 16 (adds shading for UI elements)
3. If still unclear: try scale: 0.75 or full color
4. Remember: cache what works per window/app for the rest of the session

This way the AI learns the right settings per app without wasting tokens on oversized images.

Features

• 5 capture modes: Fullscreen, active window, specific window (by title), interactive region selection, coordinate-based rectangle
• Cross-platform: Windows (PowerShell + System.Drawing), macOS (sips + ImageMagick), Linux (ImageMagick)
• Multi-monitor: Select which monitor to capture
• Delay: Wait N seconds before capturing (e.g., to open a menu first)
• Size reporting: Shows original → optimized size and percentage saved
• Auto-path: Default saves to temp directory with fixed filename
• No index required: Works standalone, no .aidex/ needed

Interactive Viewer

Explore your indexed project visually in the browser:

aidex_viewer({ path: "." })

Opens http://localhost:3333 with:

• Interactive file tree - Click to expand directories
• File signatures - Click any file to see its types and methods
• Live reload - Changes detected automatically while you code
• Git status icons - See which files are modified, staged, or untracked
• Search tab - Semantic / exact / hybrid search across code, docs, tasks & notes, with the optional LLM layer (translate + rerank)
• Live tab - Live Debug Dashboard: fixed-slot widgets (plots, gauges, progress) plus interactive sliders, switches and buttons that drive a running program back through the /control channel
• Logs tab - Live log stream from Log Hub with filters (level, source, text search)
• Tasks tab - View and manage your task backlog
• Settings tab - Configure embeddings & the LLM provider (privacy switch defaults to off)

Debug Dashboard — live, two-way

The Live tab is a live dashboard with fixed slots: send the same id again and the value updates in place instead of scrolling away. Interactive slider/number/toggle/button widgets flow back to the source (HTTP /control, or aidex_log control_set so the AI can tune a running program too). A button carries a press counter, not a flag, so a source polling at its own pace never misses a click. Full guide: docs/loghub-panel-dashboard.md.

[The Live Dashboard — plots, gauges and the four interactive control types side by side]

The Controls group holds one of each interactive type: a slider, two toggles, and a button with its press counter beside it. Scrolled further down, several sources share the same dashboard — the hub knows nothing about what any value means, so a synth firmware and a demo script coexist without either being aware of the other:

[Further down the same dashboard — gauges, plots and controls from several sources at once]

The sliders react in real time — watch the GIF:

[Tuning sliders drive the live waveform plots]

The rest of the Viewer

[AiDex Viewer - Semantic & hybrid search]

[AiDex Viewer - Settings (embeddings & LLM)]

[AiDex Viewer - Tasks]

[AiDex Viewer - Code signatures]

[AiDex Viewer - Signatures]

[AiDex Viewer - Overview]

Close with aidex_viewer({ path: ".", action: "close" })

CLI Usage

aidex scan Q:/develop       # Find all indexed projectsaidex init ./myproject      # Index a project from command line

aidex-mcp works as an alias for aidex.

Performance

Technology

• Parser: Tree-sitter - Real parsing, not regex
• Database: SQLite with WAL mode - Fast, single file, zero config
• Protocol: MCP - Works with any compatible AI

Project Structure

.aidex/                  ← Created in YOUR project├── index.db             ← SQLite database└── summary.md           ← Optional documentation
AiDex/                   ← This repository├── src/│   ├── commands/        ← Tool implementations│   ├── db/              ← SQLite wrapper│   ├── parser/          ← Tree-sitter integration│   └── server/          ← MCP protocol handler└── build/               ← Compiled output

Community

GitHub Discussions — Ask questions, share your setup, suggest ideas.

Contributing

See CONTRIBUTING.md for full details. Quick summary:

• Bug? → Open an issue
• Idea? → Start a Discussion
• New language? → Add a keyword file in src/parser/languages/ and open a PR

License

MIT License - see LICENSE

Authors

Uwe Chalas & Claude