Store anything, find it by meaning, act on it instantly.
bkmr - crate of the week 482 - memories, bookmarks, snippets, text - search it, invoke it!
Organize, find, and apply various content types:
_mem_ system tag for AI agent memory--json, --np, --stdout for pipelines and integrationsPersistent 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
Use skill/bkmr-memory. It defines a comprehensive memory protocol with taxonomy, deduplication, and session workflows.
See Agent Integration.
# 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"
# Agent memory: store and retrieve knowledge
bkmr add "Prod DB on port 5433" fact,database --title "Prod DB config" -t mem --no-web
bkmr hsearch "database config" -t _mem_ --json --np
General Usage:

Fuzzy Search with FZF:

Agent Memory:

Detailed walkthroughs: Overview | Getting Started | Search and Filter | Edit and Update | Tag Management
# 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 Installation Guide for detailed instructions and troubleshooting.
# 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
# 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
Quick Start Guide: See the Quick Start for a 5-minute tutorial.
| Command | Description |
|---|---|
search | Full-text search with tag filtering, FZF, JSON output |
hsearch | Hybrid search: FTS + semantic with RRF fusion |
sem-search | Semantic search using local embeddings (offline, no API keys) |
add | Add bookmarks (URLs, snippets, scripts, markdown, env vars) |
open | Smart action dispatch based on content type |
edit | Edit bookmarks (smart: opens source file for imports) |
update | Modify tags and custom openers |
delete | Delete bookmarks by ID |
show | Display bookmark details |
import-files | Import files/directories with frontmatter parsing |
tags | View tag taxonomy with usage counts |
info | Show configuration, database path, embedding status |
backfill | Generate missing embeddings |
clear-embeddings | Clear all embeddings and content hashes |
lsp | Start LSP server for editor snippet completion |
completion | Generate shell completions (bash, zsh, fish) |
surprise | Open random URL bookmarks |
Complete command documentation: See Basic Usage for detailed examples.
bkmr intelligently handles different content types with appropriate actions:
| Content Type | Default Action | System Tag |
|---|---|---|
| URLs | Open in browser | (none) |
| Snippets | Copy to clipboard | _snip_ |
| Shell Scripts | Interactive edit + execute | _shell_ |
| Markdown | Render in browser with TOC | _md_ |
| Environment Variables | Print for eval/source | _env_ |
| Text Documents | Copy to clipboard | _imported_ |
| Agent Memory | Display to stdout | _mem_ |
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
Comprehensive documentation is available in the bkmr Wiki:
Access your snippets directly within your editor without context switching.
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
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
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
Linux Clipboard: Uses external tools for reliable clipboard persistence.
wl-copy from wl-clipboard packagexclip (preferred) or xsel as fallbackWAYLAND_DISPLAY environment variablegit clone https://github.com/sysid/bkmr.git
cd bkmr
cargo build --release
make test
See TESTING.md for everything test-related: automated, scenario and manual editor tests.
See Development for complete contributor guide.
We welcome contributions! Please check our Contributing Guidelines to get started.
Resources:
162 followers · starred Feb 2023
217 followers · starred Dec 2023
216 followers · starred Oct 2025
148 followers · starred May 2026
Rust
97.4%
Python
1.0%
Store anything, find it by meaning, act on it instantly.
bkmr - crate of the week 482 - memories, bookmarks, snippets, text - search it, invoke it!
Organize, find, and apply various content types:
_mem_ system tag for AI agent memory--json, --np, --stdout for pipelines and integrationsPersistent 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
Use skill/bkmr-memory. It defines a comprehensive memory protocol with taxonomy, deduplication, and session workflows.
See Agent Integration.
# 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"
# Agent memory: store and retrieve knowledge
bkmr add "Prod DB on port 5433" fact,database --title "Prod DB config" -t mem --no-web
bkmr hsearch "database config" -t _mem_ --json --np
General Usage:

Fuzzy Search with FZF:

Agent Memory:

Detailed walkthroughs: Overview | Getting Started | Search and Filter | Edit and Update | Tag Management
# 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 Installation Guide for detailed instructions and troubleshooting.
# 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
# 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
Quick Start Guide: See the Quick Start for a 5-minute tutorial.
| Command | Description |
|---|---|
search | Full-text search with tag filtering, FZF, JSON output |
hsearch | Hybrid search: FTS + semantic with RRF fusion |
sem-search | Semantic search using local embeddings (offline, no API keys) |
add | Add bookmarks (URLs, snippets, scripts, markdown, env vars) |
open | Smart action dispatch based on content type |
edit | Edit bookmarks (smart: opens source file for imports) |
update | Modify tags and custom openers |
delete | Delete bookmarks by ID |
show | Display bookmark details |
import-files | Import files/directories with frontmatter parsing |
tags | View tag taxonomy with usage counts |
info | Show configuration, database path, embedding status |
backfill | Generate missing embeddings |
clear-embeddings | Clear all embeddings and content hashes |
lsp | Start LSP server for editor snippet completion |
completion | Generate shell completions (bash, zsh, fish) |
surprise | Open random URL bookmarks |
Complete command documentation: See Basic Usage for detailed examples.
bkmr intelligently handles different content types with appropriate actions:
| Content Type | Default Action | System Tag |
|---|---|---|
| URLs | Open in browser | (none) |
| Snippets | Copy to clipboard | _snip_ |
| Shell Scripts | Interactive edit + execute | _shell_ |
| Markdown | Render in browser with TOC | _md_ |
| Environment Variables | Print for eval/source | _env_ |
| Text Documents | Copy to clipboard | _imported_ |
| Agent Memory | Display to stdout | _mem_ |
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
Comprehensive documentation is available in the bkmr Wiki:
Access your snippets directly within your editor without context switching.
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
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
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
Linux Clipboard: Uses external tools for reliable clipboard persistence.
wl-copy from wl-clipboard packagexclip (preferred) or xsel as fallbackWAYLAND_DISPLAY environment variablegit clone https://github.com/sysid/bkmr.git
cd bkmr
cargo build --release
make test
See TESTING.md for everything test-related: automated, scenario and manual editor tests.
See Development for complete contributor guide.
We welcome contributions! Please check our Contributing Guidelines to get started.
Resources:
162 followers · starred Feb 2023
217 followers · starred Dec 2023
216 followers · starred Oct 2025
148 followers · starred May 2026
Rust
97.4%
Python
1.0%