Aikd Indexed Semantic & Bm25 Code Search For Ai Agents. Give Your Ai Instant Memory Of Your Codebase. Rust | Mcp Server.

🤔 Why AIKD?

The Problem: AI coding agents are powerful but forgetful. Every new conversation starts from zero — no memory of your codebase, your patterns, your architecture.

How AIKD Compares

✨ Key Features

🔍 Search Engine

• Hybrid Search: BM25 (Tantivy) + Vector (ONNX all-MiniLM-L6-v2, 384d)
• Reciprocal Rank Fusion: Combines keyword + semantic results intelligently
• Incremental Indexing: Blake3 hashing for zero-redundancy scans
• Resource Adaptive: Auto-detects CPU/GPU and adjusts batch sizes

🤖 AI Integration

• MCP Protocol: Native support for Model Context Protocol
• 7 Built-in Tools: scan, query, embed, stats, remember, recall, status
• Auto-Registration: Works with Claude Code, Cursor, Cline, Continue, Windsurf, MiMoCode
• Session Memory: Persistent conversation context across sessions

🛠️ Developer Experience

• Single Binary: No Python, no Node, no dependencies
• File Watcher: Auto-reindex on file changes
• REST API: HTTP endpoint on port 9090 for custom integrations
• CLI First: Full control from terminal

🎬 See It In Action

$ aikd init
✅ AIKD initialized for project

$ aikd scan
📊 Indexed 847 files, 12,453 chunks in 1.2s

$ aikd query "authentication flow"
1. src/auth/login.rs (Lines 45-89, Score: 0.923)
   Implements JWT-based authentication with refresh tokens...

2. src/middleware/auth.rs (Lines 12-34, Score: 0.871)
   Validates Bearer tokens on protected routes...

3. docs/architecture/auth.md (Lines 1-25, Score: 0.845)
   Authentication flow diagram and security considerations...

📦 Installation

Recommended (One-Line)

Linux / macOS:

curl -sSf https://raw.githubusercontent.com/gelutjari/aikd/main/install.sh | bash

Windows (PowerShell):

irm https://raw.githubusercontent.com/gelutjari/aikd/main/install.ps1 | iex

Alternatives

cargo install aikd

brew install gelutjari/tap/aikd

git clone https://github.com/gelutjari/aikd.git
cd aikd
cargo build --release
cp target/release/aikd ~/.local/bin/

docker run -v $(pwd):/workspace -p 9090:9090 ghcr.io/gelutjari/aikd:latest

⚡ Quick Start (3 minutes)

Step 1: Initialize

cd your-project
aikd init

Step 2: Scan Your Codebase

aikd scan

Step 3: Search

# Keyword search (fast)
aikd query "error handling"

# Semantic search (smart)
aikd query "how does login work" --hybrid

# Get JSON output for scripting
aikd query "database connection" --json

Step 4: Connect to Your AI Agent

{
  "mcpServers": {
    "aikd": {
      "command": "aikd",
      "args": ["serve"]
    }
  }
}

# Start the daemon
aikd daemon

# Query via HTTP
curl "http://localhost:9090/api/query?q=authentication&limit=5"

🎛️ Usage Modes

                    ┌─────────────────┐
                    │   How to use    │
                    │     AIKD?       │
                    └────────┬────────┘
                             │
            ┌────────────────┼────────────────┐
            ▼                ▼                ▼
     ┌──────────┐     ┌──────────┐     ┌──────────┐
     │   CLI    │     │   MCP    │     │ REST API │
     │  Mode    │     │  Server  │     │  Daemon  │
     └──────────┘     └──────────┘     └──────────┘
     Best for:        Best for:        Best for:
     • Quick search   • AI agents      • Web apps
     • Scripts        • Claude Code    • Custom UIs
     • CI/CD          • Cursor         • Team shared

CLI Mode (default):

aikd query "rust error handling" --limit 5
aikd stats
aikd status

MCP Server (for AI agents):

aikd serve  # Starts stdio MCP server

REST Daemon (background service):

aikd daemon              # Start in background
aikd daemon foreground   # Start in foreground
aikd daemon-stop         # Stop daemon

📊 Benchmark Results

Hardware: AMD EPYC 7B13, 7.8GB RAM, NVMe SSD

Resource Usage:

CPU: ████████░░░░░░░░░░░░ 22.9%
RAM: █████░░░░░░░░░░░░░░░ 27.4%

💡 Real-world context: A human eye blink takes ~300ms. In that time, AIKD can complete 857 hybrid searches across your entire codebase.

⚙️ Configuration

Default config (~/.aikd/config.yaml):

version: 2.0.0
scan:
  include_paths: ["."]
  exclude_paths: ["node_modules", ".git", "target"]
  include_extensions: ["rs", "ts", "py", "md", "json"]
  follow_symlinks: false
chunk:
  max_tokens: 1000
  min_tokens: 100
embedding:
  enabled: true
  model: all-MiniLM-L6-v2
  batch_size: auto
server:
  rest_port: 9090
  auth_token: null
  cors_origins: ["*"]

embedding:
  enabled: true
  batch_size: 8
  device: cpu
resource:
  mode: Low

embedding:
  enabled: true
  batch_size: 64
  device: gpu
resource:
  mode: Max

scan:
  include_extensions: ["md", "txt", "rst"]
  exclude_paths: [".git"]
filter:
  max_file_size: 524288  # 512KB

server:
  rest_port: 9090
  auth_token: "your-secret-token"
  cors_origins:
    - "https://your-team-app.com"

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐
│                        AIKD v2.0.0                          │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ┌─────────┐  ┌─────────┐  ┌─────────┐  ┌─────────────┐  │
│  │  CLI    │  │  MCP    │  │  REST   │  │ File Watcher│  │
│  │ (clap)  │  │ (rmcp)  │  │ (axum)  │  │  (notify)   │  │
│  └────┬────┘  └────┬────┘  └────┬────┘  └──────┬──────┘  │
│       │            │            │               │          │
│       └────────────┴────────────┴───────────────┘          │
│                            │                                │
│  ┌─────────────────────────┴──────────────────────────┐    │
│  │                   Core Engine                       │    │
│  ├─────────────┬─────────────┬─────────────────────────┤    │
│  │  Scanner    │   Chunker   │      Session Manager    │    │
│  │ (walkdir)   │(pulldown-   │    (conversation DB)    │    │
│  │             │  cmark)     │                         │    │
│  └──────┬──────┴──────┬──────┴─────────────────────────┘    │
│         │             │                                      │
│  ┌──────┴──────┐ ┌────┴─────┐ ┌──────────────────────┐     │
│  │  Indexer    │ │ Embedder │ │     Storage           │     │
│  │  (Tantivy)  │ │ (ONNX)   │ │   (SQLite + WAL)     │     │
│  │  BM25 +     │ │ 384d     │ │   + r2d2 pool        │     │
│  │  HNSW ANN   │ │ MiniLM   │ │   + blake3 hashing   │     │
│  └─────────────┘ └──────────┘ └──────────────────────┘     │
│                                                             │
└─────────────────────────────────────────────────────────────┘

See docs/ARCHITECTURE.md for detailed breakdown.

🆘 Troubleshooting

Diagnostic Commands:

aikd status --json     # System info
aikd stats             # Index statistics
aikd daemon-pid        # Check if daemon running

aikd model download

# Change port in config
# ~/.aikd/config.yaml
server:
  rest_port: 9091

resource:
  mode: Low
  max_memory_mb: 512

🤝 Community

Get Help:

• 💬 GitHub Discussions — Ask questions
• 🐛 Issues — Report bugs
• 📧 Email: [email protected]

Contributors:

See CONTRIBUTING.md for how to contribute.

📄 License

MIT License — see LICENSE for details.