# SEOSiri-Official/biorobotics [Health: Active]

**Category:** Biology, Medicine and Bioinformatics  
**Repository:** https://github.com/SEOSiri-Official/biorobotics  
**GitHub Stars:** 0  
**Views:** 4  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/seosiri-official-biorobotics

## Description
A stateless, deterministic Bio-Robotics Core Engine converting biological data (UniProt API) to Cartesian G-code coordinates using the Model Context Protocol.  🐍 🏠 🍎 🪟 🐧

## Tools
Capabilities this server exposes over MCP:

- **fetch_genomic_data** — Queries live sequence parameters from the UniProt REST API, with a local fallback for offline or rate-limited conditions.
- **resolve_biotech_spatial_intent** — Translates assay parameters (concentration, plate scale) into immutable spatial metrics in SI base units.
- **map_plate_coordinate** — Translates alphanumeric well IDs (e.g. `A1`–`H12`) into exact millimeter offsets, per SLAS/SBS 96-well plate standards.
- **calculate_pipetting_speed** — Calibrates G-code feedrate and pressure delay from reagent viscosity and target volume.
- **calculate_dna_melting_temp** — Calculates GC-content and melting temperature (Tm) of a DNA sequence for thermal deck configuration.
- **translate_emg_to_actuation** — Translates EMG muscle signals (µV) into safe joint angles and G-code velocity profiles, with a built-in safety envelope check.

## Claude Desktop Quick Installation
Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low):

```json
"mcpServers": {
  "biorobotics": {
    "command": "npx",
    "args": ["-y","seosiri-official-biorobotics"]
  }
}
```

## Documentation

## What SEOSiri-Official/biorobotics MCP server does

SEOSiri-Official/biorobotics MCP server connects biological inputs and physiological signals to deterministic calculations for laboratory automation and robotic motion planning. It does not present itself as a clinical control system or a complete hardware controller. Instead, it returns structured values such as sequence information, spatial offsets, feedrates, delays, DNA melting temperatures, joint angles, and G-code strings.

The server is stateless. Inputs are normalized through mathematical boundaries and expressed in SI units where applicable. Plate operations can also use millimeter-scale values, while actuation outputs use Cartesian G-code conventions. The repository describes the project as a research and prototyping layer, particularly for workflows involving biological datasets, surface EMG, pipetting, and physical positioning.

## How it works

SEOSiri-Official/biorobotics MCP server communicates through Model Context Protocol JSON-RPC over standard input and output. A client invokes one of six tools with structured parameters, and the Python runtime performs the corresponding calculation or data request.

`fetch_genomic_data` queries the UniProt REST API for sequence parameters. When the service is unavailable or rate-limited, the implementation can use local fallback reference data. The remaining tools are calculation-oriented: assay concentration and plate scale become spatial metrics; a well identifier becomes a coordinate offset; viscosity and target volume become a feedrate and pressure delay; and a DNA sequence becomes GC-content and melting-temperature values.

The EMG tool maps a signal measured in microvolts to a joint angle and G-code velocity profile. It also applies the described safety-envelope check. These outputs should be treated as inputs for research or prototyping systems, not as independently validated commands for medical or assistive deployment.

## Setup and configuration

The repository requires Python 3.10 or newer. `pip` is supported, and `uv` is optional. For a local checkout, the README shows editable installation with `pip install -e .`. The repository also includes a Dockerfile for isolated execution.

An MCP client can launch the entry point at `src/main_mcp_server.py`. With `uv`, the documented direct repository configuration runs `uv run --github SEOSiri-Official/biorobotics src/main_mcp_server.py`. A cloned repository can instead be started with Python and a `PYTHONPATH` pointing to the project directory.

The protocol uses stdio, so the client must support local MCP processes. The documented compatible clients include Claude Desktop and Cursor IDE. Linux, macOS, and Windows are listed as supported platforms.

## Tools and capabilities

- `fetch_genomic_data`: Retrieves sequence parameters from UniProt, with fallback reference data for offline or rate-limited conditions.
- `resolve_biotech_spatial_intent`: Converts concentration and plate-scale inputs into immutable SI-unit spatial metrics.
- `map_plate_coordinate`: Converts alphanumeric wells such as `A1` through `H12` into offsets for SLAS/SBS 96-well plates.
- `calculate_pipetting_speed`: Computes a G-code feedrate and pressure delay from viscosity and target volume.
- `calculate_dna_melting_temp`: Computes GC-content and DNA melting temperature for thermal deck configuration.
- `translate_emg_to_actuation`: Converts EMG values into joint angles and G-code velocity profiles, including a safety-envelope result.

## Limitations and notes

The project depends on UniProt for live genomic lookups but provides fallback behavior for some unavailable requests. Its outputs are deterministic mathematical translations, not guarantees that a connected robot, pipette, thermal deck, or prosthetic mechanism will behave safely. The EMG feature is explicitly not a certified medical or prosthetic control system; clinical or assistive use requires separate regulatory validation and hardware safeguards.

The roadmap mentions closed-loop serial telemetry and capacitive liquid-level detection as future work, so those capabilities should not be assumed to be available in the current server.

_Full upstream README: https://allmcps.com/mcp/seosiri-official-biorobotics/readme_