# 🧬 WetLab-MCP

<p align="center">
  <img src="logo.png" width="300" alt="WetLab-MCP Logo">
</p>

<p align="center">
  <img src="https://img.shields.io/badge/Python-3.10%2B-blue?style=for-the-badge&logo=python" alt="Python Version">
  <img src="https://img.shields.io/badge/MCP-Protocol-orange?style=for-the-badge&logo=cloudera" alt="MCP Protocol">
  <img src="https://img.shields.io/badge/License-MIT-green?style=for-the-badge" alt="License">
  <img src="https://img.shields.io/badge/Bioinformatics-Standard-red?style=for-the-badge" alt="Bioinformatics">
</p>

---

## 🔬 Overview

**WetLab-MCP** is a professional FastMCP server designed to bridge the gap between computational discovery and wet-lab execution. It provides a comprehensive suite of tools for qPCR primer design, cloning strategy optimization, and sequence specificity analysis, all integrated directly into your AI-assisted research workflow.

Starting with the industry-standard `primer3-py` engine, WetLab-MCP ensures deterministic, high-quality assay designs without ever needing an external API for core calculations.

## 🚀 Key Features

*   **`design_qpcr_primers`**: Local, deterministic qPCR primer design enforcing standard $T_m$ and GC% constraints.
*   **`design_cloning_primers`**: Intelligent cloning strategy with automatic restriction site detection and "junk" leader recommendations for high enzyme efficiency.
*   **`design_taqman_probe`**: Automated TaqMan internal oligo design with industry-standard quenching rules (no 5' G).
*   **`analyze_multiplex_compatibility`**: All-vs-all heterodimer analysis to detect cross-reactivity in multiplex PCR or panels.
*   **`design_multi_gene_panel`**: Greedy optimization for building non-conflicting primer sets for multiple targets.
*   **`check_primer_specificity`**: Live NCBI BLAST integration (blastn-short) to verify potential off-target binding.

## 🚀 Installation & Claude Integration

WetLab-MCP can be added to **Claude Desktop** using one of the following methods.

### Method 1: Using `uvx` (Recommended)

This is the fastest way to run WetLab-MCP without manual installation. Ensure you have [uv](https://github.com/astral-sh/uv) installed.

Add this to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "WetLab-MCP": {
      "command": "uvx",
      "args": ["wetlab-mcp"]
    }
  }
}
```

### Method 2: Using `pip`

If you prefer a standard installation:

```bash
pip install wetlab-mcp
```

Then add this to your `claude_desktop_config.json`:

```json
{
  "mcpServers": {
    "WetLab-MCP": {
      "command": "python",
      "args": [
        "-m",
        "wetlab_mcp"
      ]
    }
  }
}
```

## 🧪 Tool Specifications

| Tool | Purpose | Key Inputs |
|---|---|---|
| `design_qpcr_primers` | qPCR assays | Sequence, Target $T_m$ |
| `design_cloning_primers` | Cloning/Gibson | Overhangs, Target $T_m$ |
| `design_taqman_probe` | Real-time PCR | Sequence, Primers, Probe $T_m$ |
| `check_primer_specificity` | Off-target check | Primer Sequence (Internet req.) |
| `analyze_multiplex_compatibility` | Dimer analysis | List of Primers |
| `design_multi_gene_panel` | Batch design | List of Genes ({name, seq}) |

## 🛡️ License

Distributed under the **MIT License**. See `LICENSE` for more information.

---

<p align="center">
  <b>Design by <a href="https://github.com/zaeyasa">ZaEyAsa</a></b><br>
  <i>Empowering Computational Biology with Agentic Precision</i>
</p>