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Initial commit: Vestige v1.0.0 - Cognitive memory MCP server
FSRS-6 spaced repetition, spreading activation, synaptic tagging, hippocampal indexing, and 130 years of memory research. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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README.md
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<p align="center">
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<pre>
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╚████╔╝ ███████╗███████║ ██║ ██║╚██████╔╝███████╗
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╚═══╝ ╚══════╝╚══════╝ ╚═╝ ╚═╝ ╚═════╝ ╚══════╝
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</pre>
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</p>
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<h1 align="center">Vestige</h1>
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<p align="center">
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<strong>Memory traces that fade like yours do</strong>
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</p>
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<p align="center">
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The only AI memory system built on real cognitive science.<br/>
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FSRS-6 spaced repetition. Retroactive importance. Context-dependent recall.<br/>
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All local. All free.
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</p>
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<p align="center">
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<a href="#installation">Installation</a> |
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<a href="#quick-start">Quick Start</a> |
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<a href="#features">Features</a> |
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<a href="#the-science">The Science</a>
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</p>
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<p align="center">
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<a href="https://github.com/samvallad33/vestige/releases"><img src="https://img.shields.io/github/v/release/samvallad33/vestige?style=flat-square" alt="Release"></a>
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<a href="https://github.com/samvallad33/vestige/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-MIT-blue?style=flat-square" alt="License"></a>
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<a href="https://github.com/samvallad33/vestige/actions"><img src="https://img.shields.io/github/actions/workflow/status/samvallad33/vestige/release.yml?style=flat-square" alt="Build"></a>
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</p>
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---
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## Why Vestige?
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**The only AI memory built on real cognitive science.**
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| Feature | What It Does |
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|---------|--------------|
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| **FSRS-6 Spaced Repetition** | Full 21-parameter algorithm - nobody else in AI memory has this |
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| **Retroactive Importance** | Mark something important, past 9 hours of memories strengthen too |
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| **Context-Dependent Recall** | Retrieval matches encoding context (Tulving 1973) |
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| **Memory States** | See if memories are Active, Dormant, Silent, or Unavailable |
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| **100% Local** | No API keys, no cloud, your data stays yours |
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> Other tools store memories. Vestige understands how memory actually works.
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---
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## Installation
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### From Source (Recommended)
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```bash
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git clone https://github.com/samvallad33/vestige
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cd vestige
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cargo build --release --package vestige-mcp
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```
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The binary will be at `./target/release/vestige-mcp`
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### Homebrew (macOS/Linux)
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```bash
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brew install samvallad33/tap/vestige
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```
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---
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## Quick Start
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### 1. Build Vestige
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```bash
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cargo build --release --package vestige-mcp
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```
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### 2. Configure Claude Desktop
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Add Vestige to your Claude Desktop configuration:
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**macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json`
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**Windows:** `%APPDATA%\Claude\claude_desktop_config.json`
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```json
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{
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"mcpServers": {
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"vestige": {
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"command": "/path/to/vestige-mcp",
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"args": [],
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"env": {
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"VESTIGE_DATA_DIR": "~/.vestige"
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}
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}
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}
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}
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```
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### 3. Restart Claude Desktop
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Claude will now have access to persistent, biologically-inspired memory.
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---
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## Features
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### Core
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| Feature | Description |
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|---------|-------------|
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| **FSRS-6 Algorithm** | Full 21-parameter spaced repetition (20-30% better than SM-2) |
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| **Dual-Strength Memory** | Bjork & Bjork (1992) - Storage + Retrieval strength model |
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| **Hybrid Search** | BM25 + Semantic + RRF fusion for best retrieval |
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| **Local Embeddings** | 768-dim BGE embeddings, no API required |
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| **SQLite + FTS5** | Fast full-text search with persistence |
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### Neuroscience-Inspired
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| Feature | Description |
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|---------|-------------|
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| **Synaptic Tagging** | Retroactive importance (Frey & Morris 1997) |
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| **Memory States** | Active/Dormant/Silent/Unavailable continuum |
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| **Context-Dependent Memory** | Encoding specificity principle (Tulving 1973) |
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| **Prospective Memory** | Future intentions with time/context triggers |
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| **Basic Consolidation** | Decay + prune cycles |
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### MCP Tools (25 Total)
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**Core Memory (7):**
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- `ingest` - Store new memories
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- `recall` - Semantic retrieval
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- `semantic_search` - Pure embedding search
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- `hybrid_search` - BM25 + semantic fusion
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- `get_knowledge` - Get memory by ID
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- `delete_knowledge` - Remove memory
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- `mark_reviewed` - FSRS review (1-4 rating)
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**Stats & Maintenance (3):**
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- `get_stats` - Memory statistics
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- `health_check` - System health
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- `run_consolidation` - Trigger consolidation
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**Codebase Memory (3):**
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- `remember_pattern` - Store code patterns
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- `remember_decision` - Store architectural decisions
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- `get_codebase_context` - Retrieve project context
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**Prospective Memory (5):**
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- `set_intention` - Remember to do something
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- `check_intentions` - Check triggered intentions
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- `complete_intention` - Mark intention done
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- `snooze_intention` - Delay intention
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- `list_intentions` - List all intentions
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**Neuroscience (7):**
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- `get_memory_state` - Check cognitive state
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- `list_by_state` - Filter by state
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- `state_stats` - State distribution
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- `trigger_importance` - Retroactive strengthening
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- `find_tagged` - Find strengthened memories
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- `tagging_stats` - Tagging system statistics
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- `match_context` - Context-dependent retrieval
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---
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## The Science
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### Ebbinghaus Forgetting Curve (1885)
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Memory retention decays exponentially over time:
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```
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R = e^(-t/S)
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```
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Where:
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- **R** = Retrievability (probability of recall)
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- **t** = Time since last review
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- **S** = Stability (strength of memory)
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### Bjork & Bjork Dual-Strength Model (1992)
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Memories have two independent strengths:
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- **Storage Strength**: How well encoded (never decreases)
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- **Retrieval Strength**: How accessible now (decays with time)
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Key insight: difficult retrievals increase storage strength more than easy ones.
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### FSRS-6 Algorithm (2024)
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Free Spaced Repetition Scheduler version 6. Trained on millions of reviews:
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```rust
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const FSRS_WEIGHTS: [f64; 21] = [
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0.40255, 1.18385, 3.173, 15.69105, 7.1949,
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0.5345, 1.4604, 0.0046, 1.54575, 0.1192,
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1.01925, 1.9395, 0.11, 0.29605, 2.2698,
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0.2315, 2.9898, 0.51655, 0.6621, 0.1, 0.5
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];
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```
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### Synaptic Tagging & Capture (Frey & Morris 1997)
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When something important happens, it can retroactively strengthen memories from the past several hours. Vestige implements this with a 9-hour capture window.
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### Encoding Specificity Principle (Tulving 1973)
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Memory retrieval is most effective when the retrieval context matches the encoding context. Vestige scores memories by context match.
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---
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## Comparison
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| Feature | Vestige | Mem0 | Zep | Letta |
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|---------|--------|------|-----|-------|
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| FSRS-6 spaced repetition | Yes | No | No | No |
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| Dual-strength memory | Yes | No | No | No |
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| Retroactive importance | Yes | No | No | No |
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| Memory states | Yes | No | No | No |
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| Local embeddings | Yes | No | No | No |
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| 100% local | Yes | No | No | No |
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| Free & open source | Yes | Freemium | Freemium | Yes |
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---
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## Environment Variables
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| Variable | Description | Default |
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|----------|-------------|---------|
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| `VESTIGE_DATA_DIR` | Data storage directory | `~/.vestige` |
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| `VESTIGE_LOG_LEVEL` | Log verbosity | `info` |
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---
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## Development
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### Prerequisites
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- Rust 1.75+
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### Building
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```bash
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git clone https://github.com/samvallad33/vestige
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cd vestige
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cargo build --release --package vestige-mcp
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```
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### Testing
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```bash
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cargo test --workspace
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```
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---
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## Contributing
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Contributions are welcome! Please open an issue or submit a pull request.
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---
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## License
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MIT OR Apache-2.0
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---
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<p align="center">
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<sub>Built with cognitive science and Rust.</sub>
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</p>
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