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SnipContext

License: MIT Python 3.10+ Ruff Mypy CI Contributors Last Commit Issues

SnipContext Infographic

AI-powered code snippet & context manager.

Save, search, tag, and instantly inject your best boilerplate, patterns, and context into any LLM (Claude, Cursor, Grok, Windsurf, etc.).

Local-first โ€” Open source โ€” Built for humans + AI agents

๐ŸŽง Stop Feeding Your AI Clipboard Garbage โ€” Why SnipContext exists.

SnipContext Demo

Searching, tagging, and exporting code snippets โ€” all from the terminal. Watch the animated demo (GIF)


Why SnipContext?

  • Stop rewriting the same auth flows, component patterns, or utility functions
  • Stop feeding LLMs messy or outdated code from your clipboard history
  • Build your personal/team "second brain" of high-quality, reusable code
  • Semantic search finds code by meaning, not just keywords
  • LLM-optimized exports format your snippets for maximum comprehension

Key Features

Feature Status Description
Rich snippet saving with tags, metadata, and versioning โœ… Full CRUD with soft-delete and encryption
Semantic search with local embeddings โœ… sentence-transformers + FAISS, runs offline
Hybrid search โ€” semantic + keyword fusion โœ… Configurable weights, TF-IDF + embeddings
LLM-optimized export providers โœ… Claude XML, Cursor, OpenAI, Generic Markdown
Auto-tagging via embeddings โœ… Suggests tags based on similar snippets
Similarity-based deduplication โœ… Warns when adding near-duplicate snippets
Encryption at rest โœ… Fernet (AES-128) with PBKDF2 key derivation
File watchdog / real-time indexing โœ… Auto-reindex on file changes
Plugin system โœ… Entry points for providers and exporters
CLI + Python library โœ… Use from terminal or import as a module
Git-friendly local-first storage โœ… One JSON file per snippet, easy to version

Supported LLM Providers

Provider Format Best For
Generic Markdown Universal compatibility
Claude XML documents Anthropic Claude
Cursor File-style headers Cursor IDE
OpenAI Delineated sections ChatGPT / GPT-4

Quick Start

Installation

# From PyPI with uv (recommended โ€” faster installs, better dependency resolution)
uv tool install snipcontext

# From PyPI with pip
pip install snipcontext

# From source (after cloning)
cd snipcontext
uv sync                    # install all deps (including dev)
uv run sc --help           # run without activating venv

# Or with pip (traditional)
pip install -e ".[dev]"

๐Ÿ’ก Why uv? This project uses `uv` for dependency management (`uv.lock` pinned). `uv sync` guarantees reproducible installs. `pip install` works but may resolve dependencies differently.

Or install directly from GitHub

pip install git+https://github.com/billybox1926-jpg/snipcontext.git


> **๐Ÿ“ฆ Dependency Footprint:** SnipContext's core (add, list, edit, delete, keyword search, export) has no heavy dependencies. Optional features are split into extras:
> - `pip install snipcontext[semantic]` โ€” semantic search with sentence-transformers + FAISS (~500MB, requires Rust toolchain on ARM)
> - `pip install snipcontext[encryption]` โ€” encryption at rest with Fernet/AES-128 (requires Rust toolchain on ARM)
> - `pip install snipcontext[tui]` โ€” interactive terminal UI
> - `pip install snipcontext[all]` โ€” all optional features
>
> **Lighter embedding model:** The default model is `all-MiniLM-L6-v2` (~80MB). For a lighter alternative, set `SNIPCONTEXT_EMBED_MODEL_NAME=all-MiniLM-L4-v2` (~30MB) or `SNIPCONTEXT_EMBED_MODEL_NAME=paraphrase-MiniLM-L3-v2` (~20MB) before searching.
>
> **Skip semantic at runtime:** Even with `pip install snipcontext[semantic]`, use `--no-semantic` to force keyword-only search for faster results:
> ```bash
> snipcontext search "hello world" --no-semantic
> ```
>
> **ARM / Android / Termux:** The `semantic` and `encryption` extras require Rust to build native wheels. On platforms without pre-built wheels (ARM64, Android/Termux), install the core package only and use keyword search + export features. Semantic search and encryption gracefully degrade with clear error messages when their dependencies are missing.

> **Windows Users:** The short alias `sc` is shadowed by the Windows built-in `sc.exe` (Service Control). Three workarounds are available:
>
> 1. **Full command name** โ€” always works after installation:
>    ```powershell
>    snipcontext add "print('hello')" --title "Hello" --tag python
>    ```
> 2. **Wrapper script** โ€” shipped automatically with `pip install`; adds `snipcontext.cmd` to your Scripts directory:
>    ```powershell
>    snipcontext.cmd search "hello world"
>    ```
> 3. **Shell alias** โ€” for quick access in the current session:
>    ```cmd
>    doskey snip=python -m snipcontext $*
>    ```
>
> ## Works with Hermes Agent
>
> SnipContext is built CLI-first, so [Hermes Agent](https://hermes-agent.nousresearch.com) can use it directly when running in terminal mode. Common integrations:
>
> - `export --provider generic/openai/cursor/claude` to pull snippets into a prompt
> - `edit --framework --version --source` to keep metadata current
> - `add --auto-title` for fast ingestion
>
> No Hermes-specific config is required
>
> ### Standalone Binary

Two options for running without a Python environment:

**Option 1 โ€” `uv tool` (recommended, lightweight):**

```bash
# Core features only (keyword search, export)
uv tool install snipcontext

# All features (semantic search, encryption, TUI, web)
uv tool install "snipcontext[all]"

# Use directly โ€” uv manages the venv invisibly
snipcontext add "print('hello')" --title "Hello"

Option 2 โ€” Pre-built binary (no Python needed):

Download from the latest GitHub Release. Two variants are available for each platform:

Variant Includes Size (approx.)
snipcontext-<platform> Everything (semantic, encryption, TUI, web) ~200MB
snipcontext-<platform>-minimal Core only (keyword search, export) ~80MB
# Linux / macOS
chmod +x snipcontext
./snipcontext search "hello world"

# Windows
snipcontext.exe search "hello world"

Build from source:

# Using Make
make build-binary           # full build
make build-binary-minimal   # core-only build

# Using PyInstaller directly
pip install pyinstaller
pyinstaller snipcontext.spec
# Output: dist/snipcontext (or dist/snipcontext.exe)

Security Considerations

  • Encryption at rest: Uses Fernet (AES-128-CBC with HMAC) with PBKDF2 key derivation (100k iterations). Passphrase is read from SNIPCONTEXT_ENCRYPTION_PASSPHRASE env var โ€” never pass it on the command line (shell history leak).
  • No default passphrase: If encryption is enabled but SNIPCONTEXT_ENCRYPTION_PASSPHRASE is not set, the tool raises an error rather than falling back to a known default. This prevents a false sense of security.
  • stdin for sensitive content: Use sc add --file secret.py or pipe via stdin (cat secret.py | sc add --file) to avoid shell history leaks with --encrypt.
  • Salt: Auto-generated on first use and persisted to the config file. Back up your config file to avoid losing access to encrypted snippets.
  • No network calls: All processing is local. No data leaves your machine.
# Windows: use the full command name or the .cmd wrapper
snipcontext add "print('hello')" --title "Hello" --tag python
snipcontext search "hello world"
snipcontext list
snipcontext stats

# Or run via module
python -m snipcontext add "print('hello')" --title "Hello" --tag python

Verify Installation

snipcontext --help          # or: python -m snipcontext --help
snipcontext providers       # List available export providers

Project-Local Snippets

v0.5.0+ โ€” Commit your snippet collection to git and share it with your team.

By default SnipContext stores snippets in a global directory (~/.local/share/snipcontext). You can opt into project-local mode by scaffolding a .snipcontext/ directory inside your repository:

sc init --local

This creates:

.snipcontext/
โ”œโ”€โ”€ config.yaml          # Project-specific settings
โ”œโ”€โ”€ snippets/            # Snippet storage (JSONL)
โ”œโ”€โ”€ index.faiss          # Search index (gitignored)
โ””โ”€โ”€ .gitignore           # Ignores index.faiss

Once initialized, every SnipContext command run from that directory (or any subdirectory) automatically uses the local collection. You can override the discovery order with environment variables:

Priority Source Example
1 SNIPCONTEXT_HOME env var SNIPCONTEXT_HOME=/path/to/snippets sc list
2 .snipcontext/ in CWD or ancestor sc init --local in /my/project
3 Global platform directory ~/.local/share/snipcontext

Use sc info to inspect the active mode and paths:

sc info

CLI Usage

# Add a snippet
snipcontext add "def authenticate(token):\n    return jwt.decode(token, SECRET)" \
  --title "JWT Authentication" \
  --desc "Decode and verify JWT tokens" \
  --lang python \
  --tag auth --tag jwt --tag security

> SnipContext performs a fast hash-based exact duplicate check before the
> semantic dedup step. If a snippet with identical content already exists,
> you'll be prompted before adding it again.

# Add with rich metadata (v0.3.0+)
snipcontext add "from fastapi import FastAPI" \
  --title "FastAPI App Setup" \
  --framework fastapi \
  --version "0.100+" \
  --source "https://fastapi.tiangolo.com/tutorial/first-steps/" \
  --custom "team=backend" --custom "priority=high"

# Search semantically
snipcontext search "how to validate auth tokens"

# Search by tag
snipcontext search "auth" --mode tag

# Export for Claude
snipcontext search "authentication" --provider claude --output context.xml

# List all snippets
snipcontext list

# Show stats
snipcontext stats

# Delete a snippet
snipcontext delete <snippet-id>

# Edit a snippet
snipcontext edit <snippet-id> --title "New Title" --add-tag python

# Edit metadata
snipcontext edit <snippet-id> --framework react --version "18.x" --source "https://react.dev"

# Rebuild search index
snipcontext build-index --force

# Benchmark vector latency
snipcontext benchmark index --vectors 5000 --index-type ivfpq

# Watch for file changes and auto-reindex
snipcontext watch

# Run the demo
snipcontext demo

Library Usage

from snipcontext.core.models import Snippet, SnippetMetadata, Language
from snipcontext.core.storage import StorageEngine
from snipcontext.core.search import HybridSearch
from snipcontext.config.settings import get_config

# Initialize
config = get_config()
storage = StorageEngine(config)

# Create and save a snippet
snippet = Snippet(
    content="def memoize(fn):\n    cache = {}\n    ...",
    metadata=SnippetMetadata(
        title="Memoization Decorator",
        description="Cache function results",
        language=Language.PYTHON,
    ),
    tags=["python", "decorator", "performance"],
)
storage.save(snippet)

# Search with semantic understanding
searcher = HybridSearch(config)
searcher.index_snippets(storage.list_all())
results = searcher.search("cache function results decorator")

for r in results:
    print(f"{r.score:.3f} | {r.snippet.metadata.title}")

๐Ÿ” Encryption at Rest

SnipContext supports Fernet (AES-128) encryption for sensitive snippets. When enabled, snippet content is encrypted at rest using a key derived from a passphrase via PBKDF2 (100k iterations).

Enable Encryption

# Enable encryption (required)
export SNIPCONTEXT_ENCRYPT_ENABLED=true

# Set passphrase (used for key derivation)
export SNIPCONTEXT_ENCRYPTION_PASSPHRASE="your-secure-passphrase"

# Optional: persist salt to config (auto-generated if omitted)
export SNIPCONTEXT_ENCRYPT_KEY_SALT="base64-encoded-salt"

Encrypt Snippets

# Encrypt a new snippet
snipcontext add "api_key = 'sk-12345'" \
  --title "API Key" \
  --tag secret \
  --encrypt

# Mark as sensitive (auto-enables encryption)
snipcontext add "password = 'secret123'" \
  --title "DB Password" \
  --sensitive

Decrypt for Viewing/Editing

# Decrypt for viewing
snipcontext decrypt <snippet-id>

# Encrypt an existing snippet
snipcontext encrypt <snippet-id>

Note: When encrypted, the plaintext content is cleared from storage. The encrypted_content field stores the encrypted data. Use snipcontext decrypt <id> to restore plaintext for editing.


๐Ÿ”„ Index Rebuild & Resilience

SnipContext automatically detects and recovers from index corruption. The HybridSearch engine validates index integrity on load and rebuilds automatically when needed.

Manual Rebuild

# Build or rebuild the semantic search index
snipcontext build-index

# Force rebuild (useful after corruption, dependency changes, or mode switches)
snipcontext build-index --force

Auto-Recovery

The search engine automatically:

  1. Validates index integrity on load (checks ID map lengths, matrix dimensions)
  2. Cleans up corrupted files (deletes mismatched/corrupted index files)
  3. Falls back gracefully โ€” if semantic index unavailable, runs keyword-only search
  4. Rebuilds on demand โ€” index_snippets() auto-loads existing indices before rebuilding

Watchdog / Real-time Indexing

Run snipcontext watch to monitor the snippets directory and automatically reindex when files change:

snipcontext watch

Disable via config if you prefer manual rebuilds only:

export SNIPCONTEXT_WATCHDOG_ENABLED=false

Architecture

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                  CLI (Typer + Rich)              โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚  add     โ”‚  search  โ”‚  export  โ”‚  edit/delete   โ”‚
โ”‚  list    โ”‚  stats   โ”‚  watch   โ”‚  demo          โ”‚
โ””โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
     โ”‚          โ”‚          โ”‚             โ”‚
     โ–ผ          โ–ผ          โ–ผ             โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚              Search Engine (HybridSearch)        โ”‚
โ”‚  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”  โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ” โ”‚
โ”‚  โ”‚   Semantic    โ”‚  โ”‚       Keyword            โ”‚ โ”‚
โ”‚  โ”‚  FAISS Index  โ”‚  โ”‚     TF-IDF (sklearn)     โ”‚ โ”‚
โ”‚  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜  โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜ โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚              Storage Engine                      โ”‚
โ”‚         Git-friendly JSON per snippet            โ”‚
โ”œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ค
โ”‚              Data Models (Pydantic v2)           โ”‚
โ”‚     Snippet / SnippetMetadata / Language         โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

See docs/ARCHITECTURE.md for detailed design documentation.


Roadmap

  • Core snippet CRUD with git-friendly storage
  • Semantic + hybrid search with local embeddings
  • LLM-optimized export providers (Claude, Cursor, OpenAI, Generic)
  • Rich CLI with Typer
  • Plugin system with entry points
  • Python library distribution (PyPI)
  • Auto-tagging and deduplication
  • Encryption at rest
  • File watchdog / real-time indexing
  • Import from GitHub Gists
  • Import from Git repositories
  • Snippet templates and scaffolding
  • Team sharing via git-sync
  • VS Code extension

Configuration

SnipContext uses environment variables and a YAML config file:

# Use GPU for embeddings
export SNIPCONTEXT_EMBED_DEVICE="cuda"

# Change embedding model
export SNIPCONTEXT_EMBED_MODEL_NAME="all-mpnet-base-v2"

# Adjust search weights
export SNIPCONTEXT_SEARCH_SEMANTIC_WEIGHT="0.8"

# Enable auto-tagging
export SNIPCONTEXT_AUTO_TAG_ENABLED=true

# Enable deduplication
export SNIPCONTEXT_DEDUP_ENABLED=true
export SNIPCONTEXT_DEDUP_THRESHOLD="0.95"

Or edit ~/.config/SnipContext/snipcontext.yaml:

embedding:
  model_name: "all-MiniLM-L6-v2"
  device: "cpu"

search:
  default_mode: "hybrid"
  semantic_weight: 0.7
  keyword_weight: 0.3
  top_k: 10

auto_tag:
  enabled: true
  threshold: 0.75

dedup:
  enabled: true
  threshold: 0.95

Development

# Clone
git clone https://github.com/billybox1926-jpg/snipcontext.git
cd snipcontext

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=snipcontext

# Linting
ruff check .
mypy .

# Install pre-commit hooks
pre-commit install

Documentation

See docs/ARCHITECTURE.md for detailed design documentation.

Project Structure

snipcontext/
โ”œโ”€โ”€ src/snipcontext/          # Python package
โ”‚   โ”œโ”€โ”€ __init__.py
โ”‚   โ”œโ”€โ”€ __main__.py           # python -m snipcontext
โ”‚   โ”œโ”€โ”€ cli/
โ”‚   โ”‚   โ””โ”€โ”€ main.py           # Typer CLI commands
โ”‚   โ”œโ”€โ”€ config/
โ”‚   โ”‚   โ””โ”€โ”€ settings.py       # Pydantic Settings
โ”‚   โ”œโ”€โ”€ core/
โ”‚   โ”‚   โ”œโ”€โ”€ models.py         # Pydantic data models
โ”‚   โ”‚   โ”œโ”€โ”€ storage.py        # Git-friendly JSON storage
โ”‚   โ”‚   โ”œโ”€โ”€ search.py         # Semantic + hybrid search
โ”‚   โ”‚   โ”œโ”€โ”€ auto_tag.py       # Embedding-based auto-tagging
โ”‚   โ”‚   โ””โ”€โ”€ watcher.py        # File watchdog
โ”‚   โ”œโ”€โ”€ plugins/
โ”‚   โ”‚   โ””โ”€โ”€ base.py           # Plugin base + manager
โ”‚   โ””โ”€โ”€ providers/
โ”‚       โ”œโ”€โ”€ base.py           # Provider interface
โ”‚       โ”œโ”€โ”€ claude.py         # Anthropic Claude XML
โ”‚       โ”œโ”€โ”€ cursor.py         # Cursor IDE format
โ”‚       โ”œโ”€โ”€ openai.py         # OpenAI format
โ”‚       โ””โ”€โ”€ generic.py        # Universal Markdown
โ”œโ”€โ”€ tests/                    # Test suite
โ”œโ”€โ”€ docs/                     # Documentation
โ”‚   โ”œโ”€โ”€ API.md
โ”‚   โ”œโ”€โ”€ providers.md
โ”‚   โ”œโ”€โ”€ plugins.md
โ”‚   โ””โ”€โ”€ ARCHITECTURE.md
โ”œโ”€โ”€ pyproject.toml
โ”œโ”€โ”€ CHANGELOG.md
โ””โ”€โ”€ README.md

License & Contributing

MIT License โ€” see LICENSE for details.

Contributions are welcome! Please read CONTRIBUTING.md and CODE_OF_CONDUCT.md first. New contributors should check out our Good First Issues.

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  • Tags: Python 3
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  • Uploaded via: twine/6.1.0 CPython/3.13.12

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Provenance

The following attestation bundles were made for snipcontext-0.4.1-py3-none-any.whl:

Publisher: release.yml on billybox1926-jpg/snipcontext

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