https://github.com/tradik/mddb
A minimal, lightweight structured data store designed for small applications, scripts and automation workflows. Built for simplicity, portability and low overhead.
https://github.com/tradik/mddb
automation database embedded-systems go golang key-value-store lightweight-database markdown rag-pipeline search-algorithm structured-data vector-database
Last synced: 3 months ago
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A minimal, lightweight structured data store designed for small applications, scripts and automation workflows. Built for simplicity, portability and low overhead.
- Host: GitHub
- URL: https://github.com/tradik/mddb
- Owner: tradik
- License: bsd-3-clause
- Created: 2025-11-06T23:06:58.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2026-03-26T09:10:21.000Z (3 months ago)
- Last Synced: 2026-03-26T19:11:12.674Z (3 months ago)
- Topics: automation, database, embedded-systems, go, golang, key-value-store, lightweight-database, markdown, rag-pipeline, search-algorithm, structured-data, vector-database
- Language: Go
- Homepage: http://mddb.tradik.com/
- Size: 45.6 MB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Security: SECURITY.md
- Roadmap: docs/ROADMAP.md
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README
# MDDB — AI-Native Document Database
[](https://golang.org)
[](LICENSE)
[](https://github.com/tradik/mddb/releases)
[](https://hub.docker.com/r/tradik/mddb)
[](https://hub.docker.com/r/tradik/mddb)
[](https://github.com/tradik/mddb/actions)
**AI-native document database with built-in MCP server, file upload (PDF/DOCX/HTML/ODT/RTF/TEX/YAML→Markdown), vector search, RAG pipelines, and 54 MCP tools. Plugs directly into Claude, ChatGPT, Cursor, Windsurf, and any MCP-compatible agent.**
MDDB is a document database purpose-built for AI agents and LLM workflows. Upload files (PDF, DOCX, HTML, ODT, RTF, TEX, YAML, TXT) — they're auto-converted to Markdown and embedded for semantic search. Expose everything to AI agents via 54 built-in MCP tools. Integrates with [Docling](docs/INTEGRATIONS.md#1-docling--mddb-document-ingestion), [Langflow](docs/INTEGRATIONS.md#2-langflow--mddb-visual-rag-orchestration), [OpenSearch](docs/INTEGRATIONS.md#3-opensearch--mddb-scalable-search), [SSG](docs/INTEGRATIONS.md#4-ssg--static-site-generator-from-mddb), and [wpexporter](docs/INTEGRATIONS.md#5-wpexporter--wordpress-to-mddb-migration) for production pipelines. Single ~29MB binary, zero configuration, BoltDB embedded storage, triple-protocol APIs (HTTP + gRPC + GraphQL).
## 🎯 What is MDDB?
MDDB gives your AI agents a persistent, searchable knowledge base:
- **File Upload** - Upload PDF, DOCX, HTML, ODT, RTF, TEX, YAML, TXT files — auto-converted to Markdown and indexed
- **Built-in MCP Server** - 54 tools for Claude Desktop, Cursor, Windsurf, or any MCP client
- **Vector Search** - Auto-embed documents, semantic similarity with 6 index algorithms (Flat, HNSW, IVF, PQ, SQ, BQ) + per-collection quantization (int8/int4)
- **RAG-Ready** - Hybrid search (BM25 + vector) for retrieval-augmented generation
- **Memory RAG** - Conversational memory system: store, recall, and summarize chat sessions with semantic search
- **Integrations** - [Docling](docs/INTEGRATIONS.md), [Langflow](docs/INTEGRATIONS.md), [OpenSearch](docs/INTEGRATIONS.md), [SSG](docs/INTEGRATIONS.md), [wpexporter](docs/INTEGRATIONS.md) for production pipelines
- **Zero-Shot Classification** — Classify documents against candidate labels using embeddings, no training data
- **Custom AI Tools** - Define YAML-based MCP tools for domain-specific workflows
- **Full-Text Search** - Built-in inverted index with TF-IDF, BM25, BM25F, PMISparse, 7 search modes (simple, boolean, phrase, wildcard, proximity, range, fuzzy), typo tolerance, multi-language stemming (18 languages), synonyms
- **Full Revision History** - Every update creates a new revision with complete snapshots
- **Triple Protocol APIs** - HTTP/JSON (easy), gRPC (fast), or GraphQL (flexible)
- **Automation** - Triggers, crons, webhooks with template variables and sentiment analysis
- **Real-Time Events** - Server-Sent Events (SSE) for live document change notifications
- **MCP Transports** - Streamable HTTP (`/mcp`, 2025-11-25), legacy SSE (`/sse`), and stdio
- **Built-in TLS** - Native HTTPS support, connection pooling, pprof profiling
- **Zero Configuration** - Single ~29MB binary, embedded database, no dependencies
**Perfect for:** AI agent memory, RAG pipelines, knowledge bases for LLMs, documentation chatbots, semantic search APIs, document processing (PDF/DOCX→Markdown), static site generation, WordPress migration
## 🚀 Quick Start
### Docker Compose (Recommended) - Full Stack
Start all services with one command:
```bash
git clone https://github.com/tradik/mddb.git
cd mddb
# Production mode (all services)
docker compose up -d
# Development mode (with hot reload)
make dev-start
# Development + Ollama for embeddings
make dev-start-with-ollama
```
**Services started:**
| Service | Port | Image | Description |
|---------|------|-------|-------------|
| **mddbd** | 11023 (HTTP), 11024 (gRPC), 9000 (MCP), 11443 (HTTP/3) | `tradik/mddb:latest` | Database server with MCP built-in |
| **mddb-panel** | 3000 | `tradik/mddb:panel` | React web admin UI |
### Connect to Claude / Cursor / Windsurf (MCP)
MDDB has a built-in MCP server — no extra service needed. Add to your MCP config:
```json
{
"mcpServers": {
"mddb": {
"command": "docker",
"args": [
"run", "-i", "--rm", "--network", "host",
"-v", "mddb-data:/app/data",
"-e", "MDDB_MCP_STDIO=true",
"tradik/mddb:latest"
]
}
}
}
```
That's it — your AI agent now has full access to your knowledge base with 54 built-in tools (add, search, vector search, classify, and more).
**[→ Full MCP setup guide](docs/LLM_CONNECTIONS.md)** | **[→ MCP server config](docs/MCP.md)** | **[→ Custom MCP tools](docs/CUSTOM-TOOLS.md)**
### Docker - Individual Services
```bash
# MDDB Server only
docker run -d --name mddb \
-p 11023:11023 -p 11024:11024 -p 9000:9000 \
-v mddb-data:/data \
tradik/mddb:latest
# Web Panel (connect to existing server)
docker run -d --name mddb-panel \
-p 3000:3000 \
-e VITE_MDDB_SERVER=host.docker.internal:11023 \
tradik/mddb:panel
# MCP stdio mode (for Claude Desktop, Windsurf, etc.)
docker run -i --rm --network host \
-v mddb-data:/app/data \
-e MDDB_MCP_STDIO=true \
tradik/mddb:latest
# Test it
curl http://localhost:11023/health
```
**Docker Hub:** https://hub.docker.com/r/tradik/mddb
### Install Binary
**Linux (Debian/Ubuntu):**
```bash
wget https://github.com/tradik/mddb/releases/latest/download/mddbd-latest-linux-amd64.deb
sudo dpkg -i mddbd-latest-linux-amd64.deb
sudo systemctl start mddbd
```
**macOS (Apple Silicon):**
```bash
wget https://github.com/tradik/mddb/releases/latest/download/mddbd-latest-darwin-arm64.tar.gz
tar xzf mddbd-latest-darwin-arm64.tar.gz
sudo mv mddbd-latest-darwin-arm64/mddbd /usr/local/bin/
mddbd
```
**CLI Client:**
```bash
# Linux
wget https://github.com/tradik/mddb/releases/latest/download/mddb-cli-latest-linux-amd64.deb
sudo dpkg -i mddb-cli-latest-linux-amd64.deb
# Usage
mddb-cli stats
mddb-cli add blog hello en_US -f post.md
mddb-cli search blog -f "tags=tutorial"
mddb-cli fts blog --query="getting started" --algorithm=bm25
```
**Other platforms:** See [Installation Guide](docs/INSTALLATION.md)
### Build from Source
```bash
git clone https://github.com/tradik/mddb.git
cd mddb
make build
./services/mddbd/mddbd
```
## 📦 Packages & Client Libraries
MDDB ships as a monorepo with multiple packages:
### Server & Tools
| Package | Language | Location | Description |
|---------|----------|----------|-------------|
| **mddbd** | Go | `services/mddbd/` | Database server (HTTP + gRPC + GraphQL + MCP) |
| **mddb-panel** | React/JS | `services/mddb-panel/` | Web admin panel |
| **mddb-cli** | Go | `services/mddb-cli/` | Command-line client with GraphQL support |
| **mddb-chat** | Rust | `services/mddb-chat/` | WebSocket chat server with LLM integration |
| **mddb-chat-widget** | JS/TS | `services/mddb-chat-widget/` | Embeddable JS chat widget |
### Client Libraries (REST)
Zero-dependency HTTP clients - copy a single file into your project:
| Library | Language | Location | Install |
|---------|----------|----------|---------|
| **PHP Extension** | PHP 8.0+ | `services/php-extension/mddb.php` | Copy `mddb.php` into your project |
| **Python Extension** | Python 3.8+ | `services/python-extension/mddb.py` | Copy `mddb.py` into your project |
**PHP:**
```php
require_once 'mddb.php';
$db = mddb::connect('localhost:11023', 'write');
$db->collection('blog')->add('hello', 'en_US', ['author' => ['John']], '# Hello');
$results = $db->collection('blog')->vectorSearch('cancel subscription', 5, 0.7);
```
**Python:**
```python
from mddb import MDDB
db = MDDB.connect('localhost:11023', 'write').collection('blog')
db.add('hello', 'en_US', {'author': ['John']}, '# Hello')
results = db.vector_search('cancel subscription', top_k=5)
```
### Client Libraries (gRPC)
High-performance clients generated from Protocol Buffers:
| Library | Language | Location | Description |
|---------|----------|----------|-------------|
| **Go Client** | Go | `services/mddbd/proto/` | Native Go gRPC stubs |
| **Python gRPC** | Python | `clients/python/` | Generated Python gRPC client |
| **Node.js gRPC** | Node.js | `clients/nodejs/` | Uses `@grpc/grpc-js` |
Proto definitions at `proto/mddb.proto` - generate clients for any language supported by protobuf.
### Docker Images ([Docker Hub](https://hub.docker.com/r/tradik/mddb))
| Image | Size | Description |
|-------|------|-------------|
| `tradik/mddb:latest` | ~29MB | Database server with MCP built-in (Alpine) |
| `tradik/mddb:panel` | ~88MB | Web admin panel (Node Alpine) |
| `tradik/mddb:cli` | ~8MB | CLI client (Alpine) |
### System Packages
| Format | Platform | Contents |
|--------|----------|----------|
| `.deb` | Debian/Ubuntu | mddbd + systemd unit + man page |
| `.rpm` | RHEL/CentOS/Fedora | mddbd + systemd unit + man page |
| `.tar.gz` | Any (Linux, macOS, FreeBSD) | Standalone binary |
## 💡 Key Features
### AI & Search
- ✅ **MCP Server** - 54 built-in tools via Model Context Protocol 2025-11-25 (stdio + Streamable HTTP + SSE) with tool annotations, prompts, completion, and structured output
- ✅ **File Upload** - Upload PDF, DOCX, HTML, ODT, RTF, TEX, YAML, TXT — auto-converted to Markdown (single and batch, configurable size limit)
- ✅ **Vector Search** - Semantic similarity with auto-embeddings (OpenAI, Ollama, Cohere, Voyage)
- ✅ **Full-Text Search** - Built-in inverted index with TF-IDF, BM25, BM25F, PMISparse scoring, 7 search modes (simple, boolean, phrase, wildcard, proximity, range, fuzzy), typo tolerance, metadata pre-filtering, multi-language stemming and stop words (18 languages)
- ✅ **Hybrid Search** - Sparse (BM25) + dense (vector) fusion with alpha blending or RRF
- ✅ **Aggregations** - Metadata facets (value counts) and date histograms with optional pre-filtering
- ✅ **Zero-Shot Classification** - Classify documents against candidate labels using embedding similarity
- ✅ **Custom MCP Tools** - Define YAML-based AI tools for domain-specific workflows
- ✅ **RAG Pipeline** - Built-in support for retrieval-augmented generation workflows
- ✅ **Integrations** - Docling, Langflow, OpenSearch, SSG, wpexporter ([guide](docs/INTEGRATIONS.md))
### Core Functionality
- ✅ **Document Management** - Full CRUD with metadata and collections
- ✅ **Revision History** - Complete version control with snapshots
- ✅ **Metadata Search** - Fast indexed queries with multi-value tags
- ✅ **Collection Checksum** - Lightweight CRC32 checksum per collection for cache invalidation
- ✅ **Partial Document Update** - Update metadata and/or content independently
- ✅ **Document TTL** - Time-to-live with automatic cleanup
- ✅ **Automation** - Triggers, crons, webhooks with template variables, sentiment analysis, execution logs
- ✅ **Multi-language** - Same key, multiple languages
- ✅ **Schema Validation** - JSON Schema validation per collection
- ✅ **Per-Collection Storage Backends** - Choose BoltDB (default), in-memory (ephemeral), or S3/MinIO per collection
### APIs & Protocols
- ✅ **HTTP/JSON REST** - Easy debugging, extensive docs
- ✅ **gRPC/Protobuf** - 16x faster, 70% smaller payload
- ✅ **GraphQL** - Flexible queries, schema introspection, Playground
- ✅ **CLI Client** - Full-featured command-line with GraphQL support
- ✅ **Web Panel** - React UI with REST/GraphQL toggle
### Security & Access
- ✅ **Authentication** - JWT tokens and API keys
- ✅ **Authorization** - Collection-level RBAC (Read/Write/Admin)
- ✅ **Per-Protocol Access Modes** - `MDDB_MCP_MODE=read` (MCP read-only), `MDDB_API_MODE`, `MDDB_GRPC_MODE`, `MDDB_HTTP3_MODE`
- ✅ **MCP Tool Control** - `MDDB_MCP_BUILTIN_TOOLS=false` to expose only custom YAML tools
- ✅ **User Management** - Multi-user with admin roles
- ✅ **Group Permissions** - Organize users into groups
### Replication & High Availability
- ✅ **Leader-Follower Replication** - Binlog streaming for read scaling
- ✅ **Automatic Catch-up** - Followers pull missing transactions
- ✅ **Zero-Downtime Snapshots** - Full sync for new followers
- ✅ **Cluster Monitoring** - Web panel with health and lag metrics
**[→ See all features](docs/FEATURES.md)** | **[→ Compare with alternatives](docs/COMPARISON.md)** | **[→ Performance benchmarks](docs/PERFORMANCE.md)**
## 🔄 Replication Architecture
MDDB supports leader-follower replication allowing you to scale read operations horizontally.
```mermaid
graph LR
C[Clients] -->|Writes/Reads| L[Leader]
C -->|Reads| F1[Follower 1]
C -->|Reads| F2[Follower 2]
L -->|gRPC StreamBinlog| F1
L -->|gRPC StreamBinlog| F2
```
- **Leader**: Handles writes, maintains changes in a binary log, and streams them via gRPC.
- **Followers**: Read-only, pulls transactions, reconnects automatically.
**[→ Read Full Replication Guide](docs/REPLICATION.md)**
## 🎨 Web Admin Panel
Modern React-based UI for managing documents, users, and search with REST/GraphQL API toggle.
**Features:** Browse collections, view/edit documents, vector search, user management, API mode switching (REST ↔ GraphQL), live markdown preview.
**[→ Panel documentation](docs/PANEL.md)**
## 📖 Quick Examples
### Upload Files (PDF, DOCX, HTML, ODT, RTF, TEX, YAML, TXT)
```bash
# Upload a PDF — auto-converted to Markdown
curl -X POST http://localhost:11023/v1/upload \
-F "file=@report.pdf" \
-F "collection=docs" \
-F "lang=en_US"
# Upload with custom key and metadata
curl -X POST http://localhost:11023/v1/upload \
-F "file=@manual.docx" \
-F "collection=docs" \
-F "key=user-manual" \
-F "lang=en_US" \
-F 'meta={"category":["documentation"]}'
# Batch upload multiple files
curl -X POST http://localhost:11023/v1/upload \
-F "files[]=@doc1.pdf" \
-F "files[]=@doc2.html" \
-F "files[]=@doc3.txt" \
-F "collection=docs" \
-F "lang=en_US"
```
### Add and Retrieve Documents
```bash
# Add a document
curl -X POST http://localhost:11023/v1/add \
-H 'Content-Type: application/json' \
-d '{
"collection": "blog",
"key": "hello-world",
"lang": "en_US",
"meta": {"author": ["John"], "tags": ["tutorial"]},
"contentMd": "# Hello World\n\nWelcome to MDDB!"
}'
# Get document
curl -X POST http://localhost:11023/v1/get \
-H 'Content-Type: application/json' \
-d '{"collection": "blog", "key": "hello-world", "lang": "en_US"}'
# Search by metadata
curl -X POST http://localhost:11023/v1/search \
-H 'Content-Type: application/json' \
-d '{"collection": "blog", "filterMeta": {"tags": ["tutorial"]}, "limit": 10}'
```
### Vector Search (Semantic)
```bash
# Documents auto-embedded in background
# Search by meaning, not keywords
curl -X POST http://localhost:11023/v1/vector-search \
-H 'Content-Type: application/json' \
-d '{
"collection": "kb",
"query": "how do I cancel my subscription?",
"topK": 5,
"threshold": 0.7,
"includeContent": true
}'
```
### Hybrid Search (Sparse + Dense)
Combine keyword (BM25/BM25F) and semantic (vector) search in a single query. Two merge strategies:
- **Alpha Blending**: `combined = (1-a) * BM25_score + a * vector_score` -- configurable weight
- **RRF (Reciprocal Rank Fusion)**: rank-based fusion that is robust to different score distributions
```bash
curl -X POST http://localhost:11023/v1/hybrid-search \
-H "Content-Type: application/json" \
-d '{
"collection": "docs",
"query": "machine learning",
"topK": 10,
"strategy": "alpha",
"alpha": 0.5
}'
```
### Full-Text Search (7 Modes)
FTS supports simple, boolean, phrase, wildcard, proximity, range, and fuzzy modes with auto-detection:
```bash
# Simple search with metadata pre-filtering
curl -X POST http://localhost:11023/v1/fts \
-H "Content-Type: application/json" \
-d '{
"collection": "blog",
"query": "getting started",
"limit": 10,
"algorithm": "bm25",
"filterMeta": {"category": ["tutorial"]}
}'
# Boolean search (AND, OR, NOT, +required, -excluded)
curl -X POST http://localhost:11023/v1/fts \
-H "Content-Type: application/json" \
-d '{
"collection": "blog",
"query": "rust AND performance NOT garbage",
"mode": "boolean"
}'
# Phrase search (exact sequence)
curl -X POST http://localhost:11023/v1/fts \
-H "Content-Type: application/json" \
-d '{
"collection": "blog",
"query": "\"machine learning\"",
"mode": "phrase"
}'
# Proximity search (terms within N words)
curl -X POST http://localhost:11023/v1/fts \
-H "Content-Type: application/json" \
-d '{
"collection": "blog",
"query": "\"database performance\"~5",
"mode": "proximity",
"distance": 5
}'
```
### GraphQL
```bash
# Enable GraphQL
docker run -e MDDB_GRAPHQL_ENABLED=true -p 11023:11023 tradik/mddb
# Query
curl -X POST http://localhost:11023/graphql \
-H 'Content-Type: application/json' \
-d '{
"query": "{ document(collection: \"blog\", key: \"hello-world\", lang: \"en\") { contentMd meta } }"
}'
# Interactive Playground
open http://localhost:11023/playground
```
### CLI Client
```bash
# Install CLI
wget https://github.com/tradik/mddb/releases/latest/download/mddb-cli-latest-linux-amd64.deb
sudo dpkg -i mddb-cli-latest-linux-amd64.deb
# Use CLI
mddb-cli add blog hello en_US -f post.md -m "author=John,tags=tutorial"
mddb-cli get blog hello en_US
mddb-cli search blog -f "tags=tutorial"
mddb-cli fts blog --query="getting started"
mddb-cli stats
```
**[→ More examples](docs/API_QUICK_REFERENCE.md)** | **[→ Use case examples](docs/USE_CASES.md)** | **[→ Client libraries](docs/CLIENTS.md)**
## 📚 Documentation
**🌐 [Official Website](https://mddb.tradik.com/mddb/)** - Complete documentation, downloads, examples
### Getting Started
- **[Quick Start Guide](docs/QUICKSTART.md)** - 5-minute setup
- **[Installation Guide](docs/INSTALLATION.md)** - All platforms (Linux, macOS, FreeBSD, Windows)
- **[Use Cases](docs/USE_CASES.md)** - Real-world examples
### API Documentation
- **[HTTP/JSON API](docs/API.md)** - Complete REST API reference
- **[gRPC API](docs/GRPC.md)** - High-performance protocol guide
- **[GraphQL API](docs/GRAPHQL.md)** - Flexible query language
- **[OpenAPI/Swagger](docs/openapi.yaml)** - Machine-readable spec
- **[Swagger UI](docs/swagger.html)** - Interactive API docs
### Features & Guides
- **[Vector Search](docs/EMBEDDING_PROVIDERS.md)** - Semantic search setup (OpenAI, Cohere, Voyage, Ollama)
- **[RAG Pipeline](docs/RAG-PIPELINE.md)** - Complete RAG implementation guide
- **[Search Algorithms](docs/SEARCH.md)** - TF-IDF, BM25, BM25F, PMISparse, Flat, HNSW, IVF, PQ, SQ, BQ
- **[Vector Quantization](docs/QUANTIZATION.md)** - Per-collection int8/int4 scalar quantization (4-8x compression)
- **[Server-Sent Events](docs/SSE.md)** - Real-time document change notifications with auth and rate limiting
- **[Full-Text Search](docs/FTS.md)** - Built-in inverted index with multi-language support
- **[Zero-Shot Classification](docs/ZERO-SHOT-CLASSIFICATION.md)** - Classify documents against labels using embeddings
- **[PMISparse](docs/PMISPARSE.md)** - Two-phase BM25 + PPMI query expansion (invented by Tradik Limited)
- **[Webhooks](docs/WEBHOOKS.md)** - Event-driven integration
- **[Automations](docs/AUTOMATIONS.md)** - Triggers, crons, webhooks, sentiment, template variables
- **[Authentication](docs/AUTH.md)** - JWT & API keys, RBAC
- **[Web Panel](docs/PANEL.md)** - Admin UI guide
- **[LLM Connections](docs/LLM_CONNECTIONS.md)** - MCP for Claude, ChatGPT, Ollama, DeepSeek
- **[Integrations](docs/INTEGRATIONS.md)** - Docling, Langflow, OpenSearch, SSG, wpexporter
- **[Bulk Import](docs/BULK-IMPORT.md)** - Load markdown folders
### Operations
- **[Docker Guide](docs/DOCKER.md)** - Container deployment
- **[Deployment](docs/DEPLOYMENT.md)** - Production setup
- **[Telemetry](docs/TELEMETRY.md)** - Prometheus metrics, Grafana
- **[Health Checks](docs/HEALTHCHECK.md)** - Docker & Kubernetes
- **[Performance](docs/PERFORMANCE.md)** - Benchmarks & tuning
- **[Architecture](docs/ARCHITECTURE.md)** - System design
### Development
- **[Client Libraries](docs/CLIENTS.md)** - PHP, Python, Go, Node.js
- **[Custom MCP Tools](docs/CUSTOM-TOOLS.md)** - YAML-defined AI tools
- **[Examples](docs/EXAMPLES.md)** - Code samples
- **[Contributing](CONTRIBUTING.md)** - Development guide
- **[Changelog](CHANGELOG.md)** - Version history
## 🏗️ Architecture
```
┌─────────────────────────────────────────────────────┐
│ AI Agents (Claude, ChatGPT, Cursor, Windsurf) │
│ ↕ MCP (stdio / HTTP :9000) │
├─────────────────────────────────────────────────────┤
│ Other Clients │
├──────────┬──────────┬──────────┬────────────────────┤
│HTTP/JSON │gRPC/Proto│ GraphQL │ HTTP/3 │
│ :11023 │ :11024 │ /graphql │ :11443 │
├──────────┴──────────┴──────────┴────────────────────┤
│ MDDB Server (Go) │
│ • File Upload (PDF/DOCX/HTML/TXT → Markdown) │
│ • Auto-Embeddings (OpenAI, Ollama, Cohere, Voyage) │
│ • Vector + Full-Text + Hybrid Search │
│ • Zero-Shot Classification │
│ • Automation (triggers, crons, webhooks) │
│ • JWT Auth + RBAC │
├─────────────────────────────────────────────────────┤
│ BoltDB (Embedded ACID Storage) │
│ • B+Tree index • Single-file • MVCC transactions │
└─────────────────────────────────────────────────────┘
```
**[→ Detailed architecture](docs/ARCHITECTURE.md)**
## 🗺️ Roadmap
**[→ Full roadmap](docs/ROADMAP.md)**
## 🤝 Contributing
Contributions welcome! See **[CONTRIBUTING.md](CONTRIBUTING.md)** for guidelines.
**Security issues:** See **[SECURITY.md](SECURITY.md)**
## 📄 License
BSD 3-Clause License - see **[LICENSE](LICENSE)**
## 🔗 Quick Links
- **[GitHub](https://github.com/tradik/mddb)** - Source code
- **[Docker Hub](https://hub.docker.com/r/tradik/mddb)** - Container images
- **[Releases](https://github.com/tradik/mddb/releases)** - Download binaries
- **[Documentation](https://mddb.tradik.com/mddb/)** - Full docs
- **[LLM Connections](docs/LLM_CONNECTIONS.md)** - Claude, ChatGPT, Ollama, DeepSeek, Manus, Bielik.ai
- **[Issues](https://github.com/tradik/mddb/issues)** - Bug reports