Store anything, find it by meaning, act on it instantly.

Beyond Bookmarks and Snippets: Knowledge Management for Humans and Agents

bkmr - crate of the week 482 - memories, bookmarks, snippets, text - search it, invoke it!

Organize, find, and apply various content types:

• Web URLs with automatic metadata extraction
• Code snippets for quick access and reuse
• Shell commands with immediate execution capabilities
• Markdown documents with live rendering, incl. TOC and bookmark metadata footer
• Plain text with Jinja template interpolation
• Local files and directories integration

Why bkmr?

• Developer- and agent-focused: Integrates seamlessly with workflow and toolchain
• Agent-friendly: JSON output, non-interactive mode, and _mem_ system tag for AI agent memory
• Multifunctional: Handles many content types with context-aware actions
• Intelligent: Full-text and semantic search capabilities
• Privacy-focused: Fully local — database, embeddings, and search all run offline
• Fast: 20x faster than similar Python tools
• Automation-ready: Programmatic CLI with --json, --np, --stdout for pipelines and integrations
• Editor Integration: Built-in LSP server

Agent Memory and Skill

Persistent long-term memory for AI agents. The _mem_ system tag and hsearch (hybrid FTS + semantic search) create a complete read/write memory interface:

# Agent stores memory:
bkmr add 'Prod DB is PostgreSQL 15 on port 5433' fact,database \
  --title 'Production database config' -t mem --no-web

# Agent queries memories with natural language (hybrid search)
bkmr hsearch "database configuration" -t _mem_ --json --np

# All output is structured JSON — designed for programmatic consumption

Install the bkmr-memory skill into your agent's skills directory. It defines a comprehensive memory protocol with taxonomy, deduplication, and session workflows. The copy embedded in the binary matches its CLI flags:

bkmr skill install ~/.claude/skills    # or ~/.agents/skills, or any agent's skills dir
# alternative, tracks the latest release:
gh skill install sysid/bkmr bkmr-memory --agent claude-code --scope user

See Agent Integration.

Quick Examples

# Quick fuzzy search with interactive selection
bkmr search --fzf

# Add URL with automatic metadata extraction
bkmr add https://example.com tag1,tag2

# Store code snippet
bkmr add "SELECT * FROM users" sql,_snip_ --title "User Query"

# Shell script with interactive execution
bkmr add "#!/bin/bash\necho 'Hello'" utils,_shell_ --title "Greeting"

# Render markdown in browser with TOC
bkmr add "# Notes\n## Section 1" docs,_md_ --title "Project Notes"

# Import files with frontmatter
bkmr import-files ~/scripts/ --base-path SCRIPTS_HOME

# Local semantic search (no API keys needed)
bkmr sem-search "containerized application security"

Screenshots

General Usage:

Fuzzy Search with FZF:

Agent Memory:

Detailed walkthroughs: Overview | Getting Started | Search and Filter | Edit and Update | Tag Management

Getting Started

Installation

# Via cargo
cargo install bkmr

# Via pip/pipx/uv
pip install bkmr

# Via brew
brew install bkmr
export ORT_DYLIB_PATH=/opt/homebrew/lib/libonnxruntime.dylib

See Getting Started for details and Troubleshooting if it fails.

Initial Setup

# Generate configuration
bkmr --generate-config > ~/.config/bkmr/config.toml

# Create database
bkmr create-db ~/.config/bkmr/bkmr.db

# Optional: Configure location
export BKMR_DB_URL=~/path/to/db

First Use

# Add your first bookmark
bkmr add https://github.com/yourusername/yourrepo github,project

# Search and find
bkmr search github

# Interactive fuzzy search
bkmr search --fzf

5-minute tutorial: Getting Started.

Command Reference

Complete command documentation: See Basic Usage for detailed examples.

Smart Content Actions

bkmr intelligently handles different content types with appropriate actions:

Rule: A bookmark can have at most one system tag. Local files without a system tag open with the default application.

Learn more: Content Types | Core Concepts

Documentation

Comprehensive documentation is available in the bkmr Wiki:

• Getting Started and Core Concepts
• Basic Usage, Content Types, Search and Discovery
• Configuration, Template Interpolation, Advanced Workflows
• Agent Integration, Editor Integration
• Troubleshooting, Development

Editor Integrations

Access your snippets directly within your editor without context switching.

Neovim Plugin (Recommended)

bkmr-nvim provides visual interface with zero configuration.

{
  "sysid/bkmr-nvim",
  dependencies = { "nvim-lua/plenary.nvim" },
  config = function()
    require("bkmr").setup() -- Zero config required!
  end,
}

Features: Visual snippet browser, in-editor editing, automatic LSP setup, custom commands

Built-in LSP Server

The LSP server does one job: Putting _snip_ bookmarks into the editor's completion list. Compatible with VS Code, Vim, Emacs, Sublime, and any LSP-compatible editor.

# Start LSP server
bkmr lsp

# Disable template interpolation if needed
bkmr lsp --no-interpolation

Features: Automatic completion, language-aware filtering, universal snippets, template interpolation

IntelliJ Platform Plugin

bkmr-intellij-plugin for all JetBrains IDEs.

Features: Seamless LSP integration, Tab navigation, works in IntelliJ IDEA, PyCharm, WebStorm, CLion, RustRover, and all JetBrains IDEs

Complete documentation: Editor Integration

Platform Compatibility

Linux Clipboard: Uses external tools for reliable clipboard persistence.

• Wayland: Uses wl-copy from wl-clipboard package
• X11: Uses xclip (preferred) or xsel as fallback
• Auto-detection: Detects display server via WAYLAND_DISPLAY environment variable

Development

Building from Source

git clone https://github.com/sysid/bkmr.git
cd bkmr
cargo build --release

Running Tests

make test

See TESTING.md for everything test-related: automated, scenario and manual editor tests.

See Development for architecture and build details.

Community and Contributions

We welcome contributions! Please check our Contributing Guidelines to get started.

Resources:

• GitHub: https://github.com/sysid/bkmr
• Issues: https://github.com/sysid/bkmr/issues
• Wiki: https://github.com/sysid/bkmr/wiki
• Discussions: https://github.com/sysid/bkmr/discussions