Aikd

gelutjari2stars

Indexed semantic & BM25 code search for AI agents. Give your AI instant memory of your codebase. Rust | MCP Server.

1# Aikd

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Last checked: 2026-10-28

Stars: 2
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Aikd?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Aikd need an API key?

No required environment variable is listed on this record.

What transport does Aikd use?

Aikd runs locally over stdio.

When was Aikd last checked?

Last checked 2026-10-28. Indexed semantic & BM25 code search for AI agents. Give your AI instant memory of your codebase. Rust | MCP Server.

From the publisher

Documentation

🧠 AIKD

The Ultra-Fast Local Memory Layer for AI Coding Agents

Give Claude, Cursor, and Cline instant memory of your entire codebase. Written in Rust. Zero cloud dependency. Search 10,000 chunks in 0.21ms.

Install • Quick Start • Demo • Docs

🤔 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.

Pain Point	Without AIKD	With AIKD
😵 Context Amnesia	Agent asks "what does this file do?" every session	Instant recall of entire codebase
🐌 Slow Search	Python-based RAG takes 500ms+ per query	Rust-powered BM25+Vector in 0.21ms
☁️ Cloud Dependency	Your code sent to external servers	100% local, zero data leaves your machine
🔧 Complex Setup	Install Python, pip, CUDA, models...	Single binary, one command install

How AIKD Compares

Feature	`grep`	LlamaIndex	ai-devkit	AIKD
Speed	Fast	Slow	Medium	⚡ 0.21ms
Semantic Search	❌	✅	✅	✅ Hybrid
Local Only	✅	❌	❌	✅ 100%
MCP Native	❌	❌	❌	✅ Built-in
Memory Usage	Low	High (Python)	High	📊 27% RAM
Setup Time	0s	~10min	~5min	⏱️ 30s

✨ 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 Demo

$ 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

Creates ~/.aikd/config.yaml with smart defaults based on your project type (Rust, Node, Python, Go). It detects .git, Cargo.toml, package.json, etc. and sets appropriate file filters.

Step 2: Scan Your Codebase

aikd scan

Walks directory tree (skipping node_modules, .git, target, etc.)
Chunks files by semantic boundaries (functions, headings)
Generates BM25 index (Tantivy) and vector embeddings (ONNX)
Stores everything in local SQLite database

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

AIKD auto-registers via MCP. Just restart your AI agent after running aikd scan.

The MCP config is at ~/.aikd/mcp.json:

{
  "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

AIKD Benchmarks

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

Operation	Time	Throughput
Index 1,000 files	144ms	6,934 files/s
BM25 Search	0.21ms	4,762 queries/s
Hybrid Search	0.35ms	2,857 queries/s
Concurrent (500)	28ms	17,669 queries/s
Embedding (batch)	12ms/batch	~800 chunks/s

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 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

Run aikd scan first
Check aikd stats to verify files indexed
Try broader search terms
Check include_extensions in config

aikd model download

This downloads ~90MB ONNX model to ~/.local/share/aikd/model/.

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

Or stop existing process: aikd daemon-stop

Set resource mode to Low:

resource:
  mode: Low
  max_memory_mb: 512

Check ~/.aikd/mcp.json exists
Restart your AI agent
Verify aikd serve works: echo '{"jsonrpc":"2.0","method":"initialize","id":1}' | aikd serve

Install Visual C++ Redistributable.

🤝 Community

Get Help:

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

Contributors:

Contribution	Who
🏗️ Architecture & Core	@gelutjari
🔒 Security Audit	AI-assisted (MiMo)
⚡ Performance Optimization	Community
📖 Documentation	Community

See CONTRIBUTING.md for how to contribute.

📄 License

MIT License — see LICENSE for details.

⭐ Star this repo if AIKD helps your AI agents remember!

Aikd

gelutjari2stars

Indexed semantic & BM25 code search for AI agents. Give your AI instant memory of your codebase. Rust | MCP Server.

Knowledge Memory Developer Tools

Install Run on PlugMCP

GitHub

Run on PlugMCP

1# Aikd

README.mdMCP server

Transport: stdio
Status: Local

Power your agent

Add this server

Install from the publisher. Not a PlugMCP endpoint.

Run on PlugMCP

Host a copy with our keys and logs.

No packaged release in the registry yet. Follow the repository README.

RepositoryPublisher installStep-by-step: add this in Claude

Remote URL or a command on your machine? How the two installs differ

Run on PlugMCP

Host a copy with our keys and logs.

A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.

Launch

Server facts

Local

Transport: stdio
Last checked: 2026-10-28

Stars: 2
Tools: —
Uptime: —

Tools

No tool list yet. Remote servers get one after the first health check.

FAQ

Questions

How do I install Aikd?

Copy the stdio config for Cursor, Claude Desktop, Claude Code, or VS Code on this page. It uses the publisher's install, not a PlugMCP proxy.

Does Aikd need an API key?

No required environment variable is listed on this record.

What transport does Aikd use?

Aikd runs locally over stdio.

When was Aikd last checked?

Last checked 2026-10-28. Indexed semantic & BM25 code search for AI agents. Give your AI instant memory of your codebase. Rust | MCP Server.

From the publisher

Documentation

🧠 AIKD

The Ultra-Fast Local Memory Layer for AI Coding Agents

Give Claude, Cursor, and Cline instant memory of your entire codebase. Written in Rust. Zero cloud dependency. Search 10,000 chunks in 0.21ms.

Install • Quick Start • Demo • Docs

🤔 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.

Pain Point	Without AIKD	With AIKD
😵 Context Amnesia	Agent asks "what does this file do?" every session	Instant recall of entire codebase
🐌 Slow Search	Python-based RAG takes 500ms+ per query	Rust-powered BM25+Vector in 0.21ms
☁️ Cloud Dependency	Your code sent to external servers	100% local, zero data leaves your machine
🔧 Complex Setup	Install Python, pip, CUDA, models...	Single binary, one command install

How AIKD Compares

Feature	`grep`	LlamaIndex	ai-devkit	AIKD
Speed	Fast	Slow	Medium	⚡ 0.21ms
Semantic Search	❌	✅	✅	✅ Hybrid
Local Only	✅	❌	❌	✅ 100%
MCP Native	❌	❌	❌	✅ Built-in
Memory Usage	Low	High (Python)	High	📊 27% RAM
Setup Time	0s	~10min	~5min	⏱️ 30s

✨ 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 Demo

$ 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

Creates ~/.aikd/config.yaml with smart defaults based on your project type (Rust, Node, Python, Go). It detects .git, Cargo.toml, package.json, etc. and sets appropriate file filters.

Step 2: Scan Your Codebase

aikd scan

Walks directory tree (skipping node_modules, .git, target, etc.)
Chunks files by semantic boundaries (functions, headings)
Generates BM25 index (Tantivy) and vector embeddings (ONNX)
Stores everything in local SQLite database

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

AIKD auto-registers via MCP. Just restart your AI agent after running aikd scan.

The MCP config is at ~/.aikd/mcp.json:

{
  "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

AIKD Benchmarks

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

Operation	Time	Throughput
Index 1,000 files	144ms	6,934 files/s
BM25 Search	0.21ms	4,762 queries/s
Hybrid Search	0.35ms	2,857 queries/s
Concurrent (500)	28ms	17,669 queries/s
Embedding (batch)	12ms/batch	~800 chunks/s

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 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

Run aikd scan first
Check aikd stats to verify files indexed
Try broader search terms
Check include_extensions in config

aikd model download

This downloads ~90MB ONNX model to ~/.local/share/aikd/model/.

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

Or stop existing process: aikd daemon-stop

Set resource mode to Low:

resource:
  mode: Low
  max_memory_mb: 512

Check ~/.aikd/mcp.json exists
Restart your AI agent
Verify aikd serve works: echo '{"jsonrpc":"2.0","method":"initialize","id":1}' | aikd serve

Install Visual C++ Redistributable.

🤝 Community

Get Help:

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

Contributors:

Contribution	Who
🏗️ Architecture & Core	@gelutjari
🔒 Security Audit	AI-assisted (MiMo)
⚡ Performance Optimization	Community
📖 Documentation	Community

See CONTRIBUTING.md for how to contribute.

📄 License

MIT License — see LICENSE for details.

⭐ Star this repo if AIKD helps your AI agents remember!