Install
Three ways to run this device. Each one serves its fake backend: no instrument, no simulator install and no upstream checkout.
OpenAI4S (one command)
openai4s lab add labs/fredrik-qi__fork_fluent_sila2_connectorInstalls the device into the OpenAI4S Lab on its fake backend and starts it. First time? See setup below.
Or, in the workbench, open the Lab tab → Market → Install.
Standalone MHS endpoint
git clone --depth 1 https://github.com/PKU-YuanGroup/OpenMHS.git && cd OpenMHS
PYTHONPATH=MHS/sdk/src python3 -m mhs serve labs/fredrik-qi__fork_fluent_sila2_connector --port 7400
# in a second terminal, from the same directory:
PYTHONPATH=MHS/sdk/src python3 -m mhs describe --endpoint http://127.0.0.1:7400Serves the device as an MHS endpoint on port 7400 from an OpenMHS clone (Python 3.10 or later, standard library only); describe prints what it offers.
Any MCP host (Claude Desktop, Cursor, …)
{
"mcpServers": {
"fork-fluent-sila2-connector": {
"command": "python3",
"args": [
"-m",
"mhs",
"serve",
"labs/fredrik-qi__fork_fluent_sila2_connector",
"--mcp"
],
"env": {
"PYTHONPATH": "/path/to/OpenMHS/MHS/sdk/src"
}
}
}
}Add this server to the host's MCP configuration and replace /path/to/OpenMHS with the path of your OpenMHS clone. The host starts the server and talks to it on stdin and stdout.
What it does
Measures
stateprogresslast_errorrunnable_methodsvariable_names
Adjusts
Nothing declared.
Actions
start_fluent- Start FluentControl or attach to a running instance without credentials; the connector may wait without a timeout and then prepares the method 'Method to prepare'
prepare_method- Prepare a FluentControl method; the connector deletes the Journaling/000 and Journaling/ToDelete directories before preparing
run_method- Run the currently prepared FluentControl method
pause_run- Pause the current FluentControl method; this is not the safe-state stop
resume_run- Resume a method paused by pause_run
stop_method- Stop the running method (SilaFluentController.StopMethod) and confirm that State reads RunModeRunFinished or EditMode; it takes no input
aspirate- Aspirate with the connector's fixed 8-tip A1 selection; it requires a live execution channel and passes the volume, labware, liquid class and well offset through unchanged
dispense- Dispense with the connector's fixed A1-H1 8-tip selection; it requires a live execution channel and passes the volume, labware, liquid class and well offset through unchanged
drop_tips- Drop the mounted disposable tips into the named labware
set_location- Set the location of a labware on the worktable
transfer_labware- Transfer labware on the worktable with the RGA
transfer_labware_back_to_base- Transfer labware back to the spot where it was added to the worktable
set_variable_value- Set a variable of the prepared method and read it back
Names as the driver declares them. Units, limits and the safety declaration are in the package's REFERENCE.md.
First-time setup
The OpenAI4S workbench with the OpenMHS lab, from a source checkout:
# OpenAI4S workbench with the OpenMHS lab (source checkout)
git clone --recursive https://github.com/PKU-YuanGroup/OpenAI4S.git
cd OpenAI4S && ./setup.sh && source .venv/bin/activate
openai4s lab add labs/fredrik-qi__fork_fluent_sila2_connector
openai4s serve # open the Lab tabThe standalone endpoint and the MCP server need only an OpenMHS clone and Python 3.10 or later. More in the market's getting-started guide and on the OpenAI4S host page.
Source and evidence
- Pinned commit
4a2f857c619c- Licence
- BSD-3-Clause
- Stars
- 0
- Evidence
contract_checkedon the fake backend- Backends
- fake, hardware
The driver package MHS/drivers/labs/fredrik-qi__fork_fluent_sila2_connector wraps the upstream code at the pinned commit. Its REFERENCE.md documents the full contract: every value, action, unit, limit and the safety declaration.