# 📝 Scribe MCP Server
<div align="center">
**[](tests/)**
**[](docs/whitepapers/)**
**[](LICENSE)**
*Enterprise-grade documentation governance for AI-powered development — by Corta Labs*
**Drop-in ready** • **13+ specialized templates** • **Zero-config SQLite** • **Production-tested**
</div>
---
## ✨ Update v2.1.1 (Diff Editor, Readable Output & ANSI Colors)
Scribe MCP 2.1.1 introduces foundational document lifecycle upgrades, including a fully automated YAML frontmatter engine with round-trip safety, canonical metadata defaults, and extensible schema support. Frontmatter is created on first edit if missing, auto-updates `last_updated`, and supports explicit overrides without breaking existing fields. These changes establish a metadata plane separate from document body content, enabling safe diff operations, deterministic header/TOC tooling, and template-driven document creation.
**New: Enhanced Readable Output (Phase 1.5/1.6)**
- **ANSI Color Support**: Tool output now renders with colors in Claude Code/Codex - cyan boxes, green line numbers, bold titles
- **Green Line Numbers**: Clean ` 1. content` format with dot separator, matching Claude's native Read tool style
- **CallToolResult Fix**: Workaround for Issue #9962 - returns TextContent-only for proper newline rendering
- **Config-Driven Colors**: Enable/disable via `use_ansi_colors: true` in `.scribe/config/scribe.yaml`
- **5-Char Line Padding**: Consistent line number width for improved readability
Structured edits are now the default path: agents express intent, the server compiles and applies deterministic mutations, and diagnostics remain explicit. Structural actions no longer auto-heal doc targets; if a doc key is not registered, the action fails with `DOC_NOT_FOUND` rather than redirecting the write.
- `manage_docs` now supports **apply_patch** (structured by default) and **replace_range** for precise edits.
- `apply_patch` supports `edit` payloads in structured mode; `patch_mode="unified"` opts into raw unified diffs.
- `patch_source_hash` enforces stale-source protection for patches.
- Reminder system teaches **scaffold-only** `replace_section`, preferring structured/line edits.
- New doc lifecycle actions: `normalize_headers`, `generate_toc`, `create_doc`, `validate_crosslinks`.
- `create_doc` builds documents from content/body/snippets/sections; users do **not** supply Jinja. Multiline bodies are preserved. Use `metadata.register_doc=true` only when you want the new doc added to the project registry.
- `validate_crosslinks` is read-only diagnostics (no write, no doc_updates log).
- `normalize_headers` supports ATX headers with or without space and Setext (`====` / `----`), skipping fenced code blocks. Output is canonical ATX.
- `generate_toc` uses GitHub-style anchors (NFKD normalization, ASCII folding, emoji removal, punctuation collapse, de-duped suffixes).
- Structural actions validate doc keys against the registry and fail hard on unknown docs (no silent redirects).
- `read_file` tool provides repo-scoped file reads with scan/chunk/page/search modes and provenance logging.
- `scribe_doctor` reports repo root, config, plugin status, and vector readiness for faster diagnostics.
- `manage_docs` now supports semantic search via `action="search"` with `search_mode="semantic"`, including doc/log separation and `doc_k`/`log_k` overrides.
- Vector indexing now prefers registry-managed docs only; log/rotated-log files are excluded from doc indexing.
- Reindex supports `--rebuild` (clear index), `--safe` (low-thread fallback), and `--wait-for-drain` to block until embeddings are written.
Example (structured default):
```json
{
"action": "apply_patch",
"doc": "architecture",
"edit": {
"type": "replace_range",
"start_line": 12,
"end_line": 12,
"content": "Updated line\n"
}
}
```
Example (unified diff mode, compiler output only):
```json
{
"action": "apply_patch",
"doc": "architecture",
"patch": "<compiler output>",
"patch_mode": "unified"
}
```
## 🚀 Why Scribe MCP?
Scribe transforms how AI agents and developers maintain project documentation. Instead of scattered notes and outdated docs, Scribe provides **bulletproof audit trails**, **automated template generation**, and **cross-project intelligence** that keeps your entire development ecosystem in sync.
**Perfect for:**
- 🤖 **AI Agent Teams** - Structured workflows and quality grading
- 🏢 **Enterprise Teams** - Audit trails and compliance documentation
- 👨💻 **Solo Developers** - Automatic documentation that actually works
- 📚 **Research Projects** - Structured logs and reproducible reports
**Immediate Value:**
- ✅ **30-second setup** - Drop into any repository and start logging
- 🎯 **18+ specialized templates** - From architecture guides to bug reports
- 🔍 **Cross-project search** - Find patterns across your entire codebase
- 📊 **Agent report cards** - Performance grading for AI workflows
- 🛡️ **Bulletproof storage** - Atomic operations with crash recovery
## ⚡ Quick Start
**Get Scribe running in under 60 seconds (MCP-first, CLI optional):**
### 1️⃣ Install Dependencies
```bash
# Clone and navigate to Scribe
git clone <your-repo-url>
cd scribe_mcp
# Set up Python environment
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install 16 production-ready dependencies
pip install -r requirements.txt
```
### 2️⃣ Add Scribe MCP Server to Claude Code, Codex
- Codex CLI registration example:
```bash
codex mcp add scribe \
--env SCRIBE_STORAGE_BACKEND=sqlite \
-- bash -lc 'cd /home/path/to/scribe_mcp && exec python -m server'
```
- Claude Code registration example:
```bash
claude mcp add scribe \
--env SCRIBE_STORAGE_BACKEND=sqlite \
-- bash -lc 'cd /home/path/to/scribe_mcp && exec python -m server'
```
For Global MCP
```bash
claude mcp add scribe --scope user --env SCRIBE_STORAGE_BACKEND=sqlite -- bash -lc 'cd /home/path/to/scribe_mcp && exec python -m server'
```
Once connected from Claude / Codex MCP:
- Use **`set_project`** to register/select a project and bootstrap dev_plan docs (pass `root=/abs/path/to/repo` to work in any repo).
- Use **`append_entry`** for all logging (single/bulk).
- Use **`manage_docs`** for architecture/phase/checklist updates. **2.1.1** introduces diff edits.
- Use **`read_file`** for safe, auditable file reads (scan/chunk/page/search).
- Use **`scribe_doctor`** for readiness checks (repo root, config, vector index status).
- Use **`read_recent` / `list_projects`** to resume context after compaction.
**Automatic log routing (BUG / SECURITY)**
- `status=bug` (or a bug emoji) will also write to `BUG_LOG.md` when required meta is present (`severity`, `component`, `status`).
- Security events can also tee to `SECURITY_LOG.md` (example: use a security emoji, or `--meta security_event=true,impact=...,status=...`).
- If required meta is missing, Scribe returns a teaching reminder instead of inventing data.
### 3️⃣ (Optional) Manual CLI Logging
For shell workflows or quick one-off logs, you can call the MCP-aligned CLI:
```bash
# From the scribe_mcp directory or MCP_SPINE root
python -m scribe_mcp.scripts.scribe "🚀 My project is ready!" --status success --emoji 🎉
```
Under the hood this uses `set_project` + `append_entry`, so manual usage stays in sync with the registry, SQLite mirror, and reminder system.
---
## 🎯 Try These Examples
**Project Management:**
```bash
# Log project milestones
python -m scribe_mcp.scripts.scribe "Completed authentication module" --status success --meta component=auth,tests=47
# Track bugs and issues
python -m scribe_mcp.scripts.scribe "Fixed JWT token expiry bug" --status bug --meta severity=high,component=security
```
**Research Workflows:**
```bash
# Document research findings
python -m scribe_mcp.scripts.scribe "Discovered performance bottleneck in database queries" --status info --meta research=true,impact=high
```
**Team Collaboration:**
```bash
# List all projects
python -m scribe_mcp.scripts.scribe --list-projects
# Switch between projects
python -m scribe_mcp.scripts.scribe "Starting new feature work" --project frontend --status plan
```
---
## 🛠️ Installation Options
### Prerequisites
- **Python 3.11+** - Modern Python with async support
- **pip** - Standard Python package manager
- **Optional:** PostgreSQL for team deployments (SQLite works out of the box)
### Storage Backends
**🗄️ SQLite (Default - Zero Config)**
- Perfect for solo developers and small teams
- No setup required - just run and go
- Automatic database creation and management
**🐘 PostgreSQL (Enterprise)**
- Ideal for large teams and production deployments
- Set environment variables before starting:
```bash
export SCRIBE_STORAGE_BACKEND=postgres
export SCRIBE_DB_URL=postgresql://user:pass@host:port/database
```
### MCP Integration
In all examples below, **`REPO_ROOT`** means the directory that contains the
`scribe_mcp` package (i.e., where `scribe_mcp/server.py` lives). In your
personal setup this might be `.../MCP_SPINE`, but in the public repo it will
typically just be the cloned `scribe_mcp` directory.
**For Claude Desktop (JSON config):**
```jsonc
{
"mcpServers": {
"scribe": {
// Run from REPO_ROOT so `scribe_mcp` imports resolve
"command": "bash",
"args": [
"-lc",
"cd /absolute/path/to/REPO_ROOT && exec python -m scribe_mcp.server"
],
"env": {
// Optional: override storage backend; SQLite is default
"SCRIBE_STORAGE_BACKEND": "sqlite"
}
}
}
}
```
**For Codex / Claude Code CLI:**
```bash
# From anywhere; codex will remember this configuration
codex mcp add scribe \
--env SCRIBE_STORAGE_BACKEND=sqlite \
-- bash -lc 'cd /absolute/path/to/REPO_ROOT && exec python -m scribe_mcp.server'
```
Notes:
- We intentionally **do not** bake a per-repo root into the MCP config. Scribe is multi-repo: switch repos by calling `set_project(name=..., root=/abs/path/to/repo)` (no MCP re-register needed).
- The same `bash -lc "cd REPO_ROOT && python -m scribe_mcp.server"` pattern works for any MCP client that expects a stdio server command.
---
## 🌐 Using Scribe Outside This Repo
You can run Scribe from any codebase (not just `MCP_SPINE`) by pointing it at that project’s root:
1. Start the MCP server from the Scribe codebase (once), then use `set_project(..., root=/abs/path/to/your/repo)` to target any repository.
2. Optional env vars:
- `SCRIBE_STATE_PATH=/abs/path/to/state.json` (per-user; must be writable)
- `SCRIBE_STORAGE_BACKEND=postgres` and `SCRIBE_DB_URL=postgresql://...` if you want Postgres.
3. Ensure `PYTHONPATH` includes the parent of `scribe_mcp` so imports work when launched from elsewhere.
---
## 🧠 Project Registry & Lifecycle (High-Level)
Scribe includes a **SQLite-backed Project Registry** that tracks every project’s lifecycle and documentation state:
- **Lifecycle states**: `planning`, `in_progress`, `blocked`, `complete`, `archived`, `abandoned`.
- **Core hooks**:
- `set_project` – bootstraps docs (`ARCHITECTURE_GUIDE`, `PHASE_PLAN`, `CHECKLIST`, `PROGRESS_LOG`) and ensures a registry row exists.
- `append_entry` – writes progress logs, updates activity metrics, and can auto‑promote `planning` → `in_progress` once docs + first entry exist.
- `manage_docs` – applies atomic doc updates and records baseline/current hashes and doc‑hygiene flags in the registry.
- `list_projects` – surfaces registry data (status, timestamps, counts, tags, `meta.activity`, `meta.docs.flags`) with filters like `status`, `tags`, and `order_by`.
At a glance, you can:
- See which projects are fresh, stale, or long inactive.
- Detect when architecture/phase/checklist docs are still at template state.
- Spot drift between implementation logs and documentation.
For full technical details, see `docs/whitepapers/scribe_mcp_whitepaper.md`.
---
## 📜 License & Commercial Use
Scribe MCP is **source-available** and free to use for:
- Individual developers
- Open-source contributors
- Researchers and educational use
- Small teams and small businesses that:
- Have **fewer than 25 employees**, and
- Generate **less than $1,000,000 USD in annual revenue**, and
- Are **not** selling, hosting, or packaging Scribe MCP (or derivatives) as part of a paid product or service.
You **may not** use Scribe MCP under the community license if:
- Your organization exceeds the employee or revenue limits above, or
- You embed Scribe MCP into a paid SaaS, internal platform, or commercial agent/orchestration product.
For enterprise or large-scale commercial use, contact **licensing@cortalabs.com** to obtain a commercial license.
Details:
- Current code is licensed under the **Scribe MCP License (Community + Small Business License)** in `LICENSE`.
- Earlier snapshots were MIT-licensed; see `LICENSE_HISTORY.md` for historical licensing context.
Notes:
- `.env` is auto-loaded on startup when present (via python-dotenv); shell exports/direnv still work the same.
- Overlap checks only block true path collisions (same progress_log/docs_dir). Sharing one repo root with many dev_plan folders is supported.
---
## 🎨 Template System Showcase
**Scribe includes 13+ specialized templates** that auto-generate professional documentation:
### 📋 Document Templates
- **📐 Architecture Guides** - System design and technical blueprints
- **📅 Phase Plans** - Development roadmaps with milestones
- **✅ Checklists** - Verification ledgers with acceptance criteria
- **🔬 Research Reports** - Structured investigation documentation
- **🐛 Bug Reports** - Automated issue tracking with indexing
- **📊 Agent Report Cards** - Performance grading and quality metrics
- **📝 Progress Logs** - Append-only audit trails with UTC timestamps
- **🔒 Security Logs** - Compliance and security event tracking
### 🚀 Template Features
- **🔒 Security Sandboxing** - Jinja2 templates run in restricted environments
- **📝 Template Inheritance** - Create custom template families
- **🎯 Smart Discovery** - Project → Repository → Built-in template hierarchy (precedence: `.scribe/templates` → repo custom → project templates → packs → built-ins)
- **⚡ Atomic Generation** - Bulletproof template creation with integrity verification
For a deeper dive into available variables and expected metadata per template, see `docs/TEMPLATE_VARIABLES.md`.
### Example: Generate Architecture Guide
```bash
# Auto-generate a complete architecture document
python -m scribe_mcp.scripts.scribe "Generated architecture guide for new project" --status success --meta template=architecture,auto_generated=true
```
---
## 💻 CLI Power Tools
**Scribe's command-line interface (386 lines of pure functionality)** gives you complete control:
### 🎯 Core Commands
```bash
# List all available projects
python -m scribe_mcp.scripts.scribe --list-projects
# Log with rich metadata
python -m scribe_mcp.scripts.scribe "Fixed critical bug" \
--status success \
--emoji 🔧 \
--meta component=auth,tests=12,severity=high
# Dry run to preview entries
python -m scribe_mcp.scripts.scribe "Test message" --dry-run
# Switch between projects
python -m scribe_mcp.scripts.scribe "Starting frontend work" \
--project mobile_app \
--status plan
```
### 🎨 Rich Features
- **🎭 Emoji Support** - Built-in emoji mapping for all status types
- **📊 Metadata Tracking** - Rich key=value metadata for organization
- **🔍 Multiple Log Types** - Progress, bugs, security, and custom logs
- **📅 Timestamp Control** - Override timestamps for bulk imports
- **🎯 Project Discovery** - Automatic project configuration detection
### Status Types & Emojis
- `info` ℹ️ - General information and updates
- `success` ✅ - Completed tasks and achievements
- `warn` ⚠️ - Warning messages and cautions
- `error` ❌ - Errors and failures
- `bug` 🐞 - Bug reports and issues
- `plan` 📋 - Planning and roadmap entries
---
## 🔍 Enterprise Features
### 📊 Agent Report Cards
**Performance grading infrastructure** for AI workflows:
- Quality metrics tracking and trend analysis
- Performance levels with UPSERT operations
- Automated agent evaluation and reporting
### 🔒 Security & Compliance
- **🛡️ Security Sandboxing** - Restricted Jinja2 environments with 22+ built-in controls
- **📋 Audit Trails** - Complete change tracking with metadata
- **🔐 Access Control** - Path validation and input sanitization
- **📊 Compliance Reporting** - Structured logs for regulatory requirements
### ⚡ Advanced Search
**Phase 4 Enhanced Search** capabilities:
- 🔍 **Cross-Project Validation** - Find patterns across your entire codebase
- 📊 **Relevance Scoring** - 0.0-1.0 quality filtering
- 🎯 **Code Reference Verification** - Validate referenced code exists
- 📅 **Temporal Filtering** - Search by time ranges ("last_30d", "last_7d")
### 💾 Bulletproof Storage
- **🗄️ Multi-Backend Support** - SQLite (zero-config) + PostgreSQL (enterprise)
- **⚡ Atomic Operations** - Temp-file-then-rename with fsync guarantees
- **🔄 Write-Ahead Logging** - Bulletproof crash recovery with journaling
- **✅ Integrity Verification** - Automatic corruption detection and recovery
---
## 🧠 Intelligent Reminders
**Scribe keeps your documentation in sync** with intelligent context awareness:
### 📋 Smart Reminders
Every MCP tool response includes contextual reminders about:
- 📅 **Stale Documentation** - When architecture docs need updates
- ⏰ **Overdue Logs** - Gentle nudges to maintain progress tracking
- 🎯 **Project Context** - Active project status and recent activity
- 🔄 **Drift Detection** - When implementation deviates from plans
Reminders are throttled with a short cooldown per `(repo_root, agent_id)` so you see what matters without constant repetition. If an agent gets confused, you can clear cooldowns with `set_project(reset_reminders=true)`.
If you call a project-bound tool without selecting a project, Scribe returns a “last known project” hint (including last access time) to help you recover quickly.
### ⚙️ Customization
```json
{
"name": "my_project",
"defaults": {
"reminder": {
"tone": "friendly",
"log_warning_minutes": 15,
"log_urgent_minutes": 30,
"severity_weights": {"warning": 7, "urgent": 10}
}
}
}
```
### 🌍 Environment Variables
- `SCRIBE_REMINDER_IDLE_MINUTES` - Work session reset timeout (default: 45)
- `SCRIBE_REMINDER_WARMUP_MINUTES` - Grace period after resuming (default: 5)
- `SCRIBE_REMINDER_DEFAULTS` - JSON configuration for all projects
- `SCRIBE_REMINDER_CACHE_PATH` - Optional path for reminder cooldown cache (default: `data/reminder_cooldowns.json`)
---
## 🏗️ Project Structure
```
scribe_mcp/ # 🏛️ Main Scribe MCP server
├── 📁 config/
│ ├── 📁 projects/ # Per-project configurations
│ └── 📄 mcp_config.json # Sample MCP configuration
├── 📁 docs/ # 📖 Server docs (whitepapers, guides)
├── 📁 templates/ # 🎨 Jinja2 template system
│ ├── 📁 documents/ # 13+ specialized templates
│ ├── 📁 fragments/ # Reusable template pieces
│ └── 📁 custom/ # Your custom templates
├── 📁 tools/ # 🔧 MCP tool implementations
├── 📁 storage/ # 💾 Multi-backend storage layer
├── 📁 scripts/ # 💻 CLI utilities
├── 📁 tests/ # 🧪 Comprehensive test suite
└── 📄 server.py # 🚀 MCP server entrypoint
```
**Per-repo output location (dev plans + logs)**
- Default: `<repo>/.scribe/docs/dev_plans/<project_slug>/...`
- Back-compat: if `<repo>/docs/dev_plans/<project_slug>` exists, Scribe keeps using it.
- Override: set `SCRIBE_DEV_PLANS_BASE` (example: `docs/dev_plans`) to force a different base.
---
## 🧪 Testing & Quality
**Comprehensive testing infrastructure** with 79+ test files:
### 🧪 Run Tests
```bash
# Run all functional tests (69 tests)
pytest
# Run performance tests with file size benchmarks
pytest -m performance
# Run specific test categories
pytest tests/test_tools.py
pytest tests/test_storage.py
```
### ✅ Quality Assurance
- **🔬 Functional Testing** - 69 comprehensive tests covering all core functionality
- **⚡ Performance Testing** - Optimized benchmarks for file operations
- **🛡️ Security Testing** - Template sandboxing and access control validation
- **🔄 Integration Testing** - MCP server protocol compliance verification
### 🚀 Smoke Test
```bash
# Quick MCP server validation
python scripts/test_mcp_server.py
```
---
## 💡 Real-World Use Cases
### 🤖 AI Agent Teams
**Structured workflows for AI development:**
```bash
# Research phase
python -m scribe_mcp.scripts.scribe "Research completed: authentication patterns" --status info --meta phase=research,confidence=0.9
# Architecture phase
python -m scribe_mcp.scripts.scribe "Architecture guide updated with auth design" --status success --meta phase=architecture,sections=5
# Implementation phase
python -m scribe_mcp.scripts.scribe "JWT authentication implemented" --status success --meta phase=implementation,tests=47,coverage=95%
```
### 🏢 Enterprise Documentation
**Compliance and audit trails:**
```bash
# Security events
python -m scribe_mcp.scripts.scribe "Security audit completed - all controls verified" --log security --status success --meta auditor=external,findings=0
# Change management
python -m scribe_mcp.scripts.scribe "Production deployment completed" --status success --meta version=v2.1.0,rollback_available=true
```
### 📚 Research Projects
**Structured research documentation:**
```bash
# Research findings
python -m scribe_mcp.scripts.scribe "Performance bottleneck identified in database queries" --status info --meta research=true,impact=high,evidence=query_analysis
# Experiment results
python -m scribe_mcp.scripts.scribe "A/B test results: new algorithm 23% faster" --status success --meta experiment=performance_optimization,improvement=23%
```
---
## 🔧 Troubleshooting
### Common Issues & Solutions
**🚨 MCP SDK Missing**
```bash
# Install the MCP Python SDK
pip install mcp
```
**🔧 No Tools Returned**
```bash
# Ensure all modules are properly imported
# Check that your virtual environment is active
source .venv/bin/activate
# Verify tool imports
python -c "from scribe_mcp.tools import *; print('All tools loaded')"
```
**🗄️ SQLite Permission Issues**
```bash
# Check your state/db paths are writable
echo $SCRIBE_STATE_PATH
ls -la $(dirname "$SCRIBE_STATE_PATH")
# Check the target repo is writable (Scribe writes under <repo>/.scribe/ by default)
ls -la /abs/path/to/your/repo
ls -la /abs/path/to/your/repo/.scribe || true
```
**🐍 Python Path Issues**
```bash
# Ensure you're running from the correct directory
# Run from MCP_SPINE parent directory, not inside scribe_mcp/
pwd # Should show .../MCP_SPINE/
# Test import path
python -c "import sys; sys.path.insert(0, '.'); from scribe_mcp.config.settings import settings; print('✅ Imports working')"
```
**⚡ Server Not Starting**
```bash
# Check required dependencies
pip install -r requirements.txt
# Verify server startup with timeout
timeout 5 python -m scribe_mcp.server || echo "✅ Server starts correctly"
```
### Getting Help
- **📖 Documentation**: Check `docs/whitepapers/scribe_mcp_whitepaper.md` for comprehensive technical details
- **🧪 Test Suite**: Run `pytest` to verify system functionality
- **📋 Project Templates**: Use `--list-projects` to see available configurations
- **🔍 Smoke Test**: Run `python scripts/test_mcp_server.py` for MCP validation
---
## 🤝 Contributing
**We welcome contributions!** Here's how to get started:
### 🧪 Development Workflow
```bash
# 1. Run the test suite
pytest
# 2. Verify MCP server functionality
python scripts/test_mcp_server.py
# 3. Test your changes
python -m scribe_mcp.scripts.scribe "Testing new feature" --dry-run
# 4. Log your contribution
python -m scribe_mcp.scripts.scribe "Added new feature: description" --status success --meta contribution=true,feature_type=enhancement
```
### 📋 Development Guidelines
- **✅ Test Coverage**: All new features must include tests
- **📝 Documentation**: Update relevant documentation sections
- **🔧 Integration**: Ensure MCP server compatibility
- **🛡️ Security**: Follow security best practices for templates and inputs
### 🚀 Quality Standards
- **🧪 69+ functional tests** must pass
- **⚡ Performance benchmarks** for file operations
- **🔒 Security validation** for template sandboxing
- **📋 MCP protocol compliance** verification
---
## 📚 Further Reading
### 📖 Technical Documentation
- **[📄 Whitepaper v2.1](docs/whitepapers/scribe_mcp_whitepaper.md)** - Comprehensive technical architecture
- **[🔧 API Reference](docs/api/)** - Complete MCP tool documentation
- **[🎨 Template Guide](docs/templates/)** - Custom template development
- **[🏗️ Architecture Patterns](docs/architecture/)** - System design and integration
### 🌟 Advanced Features
- **🤖 Claude Code Integration** - Structured workflows and subagent coordination
- **📊 Agent Report Cards** - Performance grading and quality metrics
- **🔍 Vector Search** - FAISS integration for semantic search
- **🔐 Security Framework** - Comprehensive access control and audit trails
### 🚀 Production Deployment
- **🐘 PostgreSQL Setup** - Enterprise-scale deployment guide
- **📈 Monitoring** - Performance tracking and alerting
- **🔄 Backup & Recovery** - Data protection strategies
- **🌐 Multi-tenant** - Organizational deployment patterns
---
## 🙏 Acknowledgments
Built with passion for better documentation and AI-human collaboration. Special thanks to:
- The **MCP protocol** team for the standardized AI tool interface
- **Jinja2** for the powerful and secure templating system
- Our **early adopters** for invaluable feedback and feature suggestions
---
<div align="center">
**🚀 Ready to transform your documentation?**
[Start Logging](#-quick-start) • [Explore Templates](#-template-system-showcase) • [Read Whitepaper](docs/whitepapers/scribe_mcp_whitepaper.md)
*Join thousands of developers and AI teams using Scribe for bulletproof documentation governance*
</div>
