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AiDex

MCP Server for persistent code indexing. Gives AI assistants (Claude, Gemini, Copilot, Cursor) instant access to your codebase. 50x less context than grep.

Install / Use

claude mcp add CSCSoftware -- npx -y github:CSCSoftware/AiDex

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

78/100

Supported Platforms

Claude Code
Claude Desktop
Cursor
GitHub Copilot
Windsurf
Gemini CLI

Tags

Our assessment of AiDex

AiDex scores 78/100 on our quality scale, 543rd of 598 Data & Analytics skills we index.

Its MCP Server is 47 KB long, well organised into 92 sections with 38 code examples: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.

It has 48 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
21/30
Structure
20/20
Description
15/15
Adoption
7/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 8 days ago, so AiDex is actively maintained.
  • Our last check on 2026-09-28 found the source still online.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

AiDex compared with similar skills

All 4 of these similar skills score higher than AiDex; compare them before choosing.

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headroomby headroomlabs-ai10079.0ktodayCLAUDE.md
CowAgentby zhayujie10047.8ktodayCLAUDE.md

Frequently asked questions

How do I install AiDex?
Run claude mcp add CSCSoftware -- npx -y github:CSCSoftware/AiDex. The install tabs above show the steps for each supported agent.
Which AI agents does AiDex work with?
It is written for Claude Code, Claude Desktop, Cursor, GitHub Copilot, Windsurf and Gemini CLI, as a MCP Server file. Other agents that read the same format can often use it too.
Is AiDex safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is AiDex still maintained?
The repository was last updated 8 days ago, so AiDex is actively maintained.

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.

<details> <summary><strong>And yes — it's still 50× more token-efficient than grep.</strong></summary>

AiDex Demo - grep vs aidex

| | Without AiDex | With AiDex | |---|---|---| | Find PlayerHealth | Grep → 200 hits in 40 files → reads 5 files → 2,000+ tokens | 1 query → 3 exact locations → ~50 tokens | | Get file structure | Reads entire 500-line file → 1,500 tokens | Signatures → classes + methods → ~80 tokens | | What changed today? | git diff + grep + context → 3,000+ tokens | Time-filtered query → ~50 tokens |

AiDex Demo GIF

</details>

What's Inside — 33 Tools in One Server

| Category | Tools | What it does | |----------|-------|--------------| | Semantic Search 🆕 | search, settings | Hybrid / semantic / exact retrieval over code, docs & workspace. Settings tab to configure embeddings + LLM layer | | Index & Identifier Search | init, query, update, remove, status | Index your project, search identifiers by name (exact/contains/starts_with), time-based filtering | | Signatures | signature, signatures | Get classes + methods of any file without reading it — single file or glob pattern | | Project Overview | summary, tree, describe, files | Entry points, language breakdown, file tree with stats, file listing by type | | Cross-Project | link, unlink, links, scan | Link dependencies, discover indexed projects | | Global Search | global_init, global_query, global_signatures, global_status, global_refresh | Search identifiers across ALL your projects — "Have I ever written X?" | | Guidelines | global_guideline | Persistent AI instructions & coding conventions — shared across all projects | | Sessions | session, note | Track sessions, detect external changes, leave notes for next session (with searchable history) | | Task Backlog | task, tasks | Built-in task management with priorities, tags, auto-logged history, and scheduled/recurring tasks | | Log Hub | log | Universal log receiver — any program sends logs via HTTP, queryable by the AI, live in Viewer | | Screenshots | screenshot, windows | Cross-platform screen capture with LLM optimization — scale + color reduction saves up to 95% tokens | | Viewer | viewer | Interactive browser UI with file tree, signatures, tasks, logs, search, and live reload |

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

<details> <summary><strong>Quick Examples</strong> — see it in action</summary>
# Find where "PlayerHealth" is defined — 1 call, ~50 tokens
aidex_query({ term: "PlayerHealth" })
→ Engine.cs:45, Player.cs:23, UI.cs:156

# All methods in a file — without reading the whole file
aidex_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 once
aidex_global_query({ term: "TransparentWindow", mode: "contains" })
→ Found in: LibWebAppGpu (3 hits), DebugViewer (1 hit)

# Leave a note for your next session
aidex_note({ path: ".", note: "Test the parser fix after restart" })

# Create a task while working
aidex_task({ path: ".", action: "create", title: "Fix edge case in parser", priority: 1, tags: "bug" })
</details>

Table of Contents

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

| Mode | What it does | When to use | |------|--------------|-------------| | exact | Identifier match (same as aidex_query) | You know the name. PlayerHealth → 3 hits | | semantic | Vector KNN over embedded code+docs+workspace | You know the concept. "how do we cache the model" → finds getQueryEmbedder | | hybrid (default) | RRF fusion of both | Mixed queries. Robust by default |

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 })

// Search
aidex_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 context
AI: grep "PlayerHealth" → 200 hits in 40 files
AI: read File1.cs, File2.cs, File3.cs...
→ 2000+ tokens consumed, 5+ tool calls

# After: precise results, minimal context
AI: 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?

| | Grep/Ripgrep | AiDex | |---|---|---| | Context usage | 2000+ tokens per search | ~50 tokens | | Results | All text matches | Only identifiers | | Precision | log matches catalog, logarithm | log finds only log | | Persistence | Starts fresh every time | Index survives sessions | | Structure | Flat text search | Knows methods, classes, types |

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

| Language | Extensions | |----------|------------| | C# | .cs | | TypeScript | .ts, .tsx | | JavaScript | .js, .jsx, .mjs, .cjs | | Rust | .rs | | Python | .py, .pyw | | C | .c, .h | | C++ | .cpp, .cc, .cxx, .hpp, .hxx | | Java | .java | | Go | .go | | PHP | .php | | Ruby | .rb, .rake | | HCL/Terraform | .tf, .tfvars, .hcl | | Kotlin | .kt, .kts | | Swift | .swift | | Astro | .astro (TypeScript frontmatter) |

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](https:/

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars48
CategoryData
Updated8d ago
Forks13

Languages

TypeScript

Trust signals

97/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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