# Opentrons OT-2 / Flex (pypi · labmcp-opentrons)

MCP server for Opentrons OT-2 and Flex liquid-handling robots (HTTP API).

- Trust score: 70/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-30

## Components

- pypi · `labmcp-opentrons`: 70/100 (this document), [markdown](https://verifymcp.io/servers/k-dense-ai-labmcp-opentrons/labmcp-opentrons.md), [page](https://verifymcp.io/servers/k-dense-ai-labmcp-opentrons/labmcp-opentrons)

## Channel facts

- Registry: `pypi`
- Package: `labmcp-opentrons`
- Version: `0.1.3`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-30.

- **Supply Chain Security**: 50/100
  - Malware scan not yet available for this package.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs hatchling.build at install time, a recognised build step with no custom scripting around it.
  - 2 of 24 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 100/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to K-Dense-AI/lab-instrument-mcps).
  - Clear OSI-approved license (Apache-2.0).
  - Actively maintained (last published 3 days ago).
  - Publishes a security disclosure policy (SECURITY.md).
- **Schema Quality & AI Usability**: 84/100
  - AI-judged instruction clarity (excellent).
  - Tool/resource definitions use about 1617 tokens (~89/item across 18 items; 18 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 17/100
  - Stability observed for 5 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 98/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 94% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 18 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 19 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the Opentrons OT-2 / Flex MCP server?

Opentrons OT-2 / Flex runs locally as a PyPI package, launched with uvx labmcp-opentrons. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add k-dense-ai-labmcp-opentrons -- uvx labmcp-opentrons
```

### Cursor

```json
{
  "mcpServers": {
    "k-dense-ai-labmcp-opentrons": {
      "command": "uvx",
      "args": [
        "labmcp-opentrons"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "k-dense-ai-labmcp-opentrons": {
      "command": "uvx",
      "args": [
        "labmcp-opentrons"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add k-dense-ai-labmcp-opentrons -- uvx labmcp-opentrons
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "k-dense-ai-labmcp-opentrons": {
      "type": "local",
      "command": [
        "uvx",
        "labmcp-opentrons"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add k-dense-ai-labmcp-opentrons --command uvx --arg labmcp-opentrons
```

### Hermes

```yaml
mcp_servers:
  k-dense-ai-labmcp-opentrons:
    command: "uvx"
    args: ["labmcp-opentrons"]
```

### Netclaw

```json
{
  "McpServers": {
    "k-dense-ai-labmcp-opentrons": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "labmcp-opentrons"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add k-dense-ai-labmcp-opentrons -t stdio -c uvx -a labmcp-opentrons
```

### Other

```json
{
  "mcpServers": {
    "k-dense-ai-labmcp-opentrons": {
      "command": "uvx",
      "args": [
        "labmcp-opentrons"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-29 (score 70, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-28 (score 69, +29)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-27 (score 40, 0)

- [functional] Package version: 0.1.2 → 0.1.3

### 2026-09-26 (score 40, −33)

- [security regression] Tool safety: pass → unverified
- [security regression] Malware scan: pass → unverified
- [security] Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- [functional regression] Capabilities: pass → unverified
- [functional regression] Tool coverage: 100 → unverified
- [functional improvement] Stability: unverified → 0.03
- [functional] First check of Schema quality: unverified
- [functional] Package version: 0.1.0 → 0.1.2
- [functional] Package version: 0.1.0 → 0.1.1

### 2026-09-25 (score 73)

First indexed and scored.

## MCP tools (18)

### `get_connection_info` (~40 tokens)

Get Connection Info

Report which instrument is connected (identity, address, simulated or real),
whether the server is read-only, and the active safety limits. Call this first.

### `get_command_log` (~46 tokens)

Get Command Log

Return the most recent raw commands sent to / replies received from the
instrument (newest last). Useful for debugging and for recording what was done.

Input parameters:

- `limit` (integer)

Output parameters:

- `result` (array)

### `reconnect` (~35 tokens)

Reconnect

Close and re-open the connection to the instrument (e.g. after it was power
cycled or a cable was re-plugged).

### `get_robot_status` (~52 tokens)

Get Robot Status

Report the robot's name, model (Flex/OT-2), software and firmware versions, lights, door and
E-stop state, and the current run. Call this first to check the robot is ready.

Output parameters:

- `current_run_id`
- `current_run_status`
- `door_must_be_closed_to_run`
- `door_open`: Front door open (None if not reported)
- `estop`: E-stop state on Flex ('disengaged' is OK); None on OT-2
- `firmware_version`
- `lights_on` (boolean)
- `model`: 'Flex' or 'OT-2'
- `name`
- `problems` (array)
- `protocol_api_versions` (string): Supported Python Protocol API versions, e.g. '2.15-2.26'
- `ready_to_start_run` (boolean): No active run, door OK, E-stop OK
- `serial`
- `software_version`: Robot software (opentrons) version
- `system_version`
- `timestamp` (string)

### `list_instruments` (~41 tokens)

List Instruments

List attached pipettes (and the Flex gripper): mount, name, channels, volume range, and whether
a tip is detected and calibration data exists.

Output parameters:

- `result` (array)

### `list_modules` (~45 tokens)

List Modules

List attached modules (Temperature Module, Heater-Shaker, Thermocycler, Magnetic Module,
Absorbance Plate Reader, ...) with live temperatures, targets, shake speed and status.

Output parameters:

- `result` (array)

### `set_lights` (~36 tokens)

Set Lights

Turn the robot's deck (rail) lights on or off.

Input parameters:

- `on` (boolean, required): True to turn the deck lights on

Output parameters:

- `result` (string)

### `home_robot` (~51 tokens)

Home Robot

Home all axes of the robot (the gantry and pipettes move to their home positions). Refused
while a run is active. Make sure nothing is in the robot's path and the door is closed.

Output parameters:

- `result` (string)

### `deactivate_modules` (~77 tokens)

Deactivate Modules

Switch attached modules off: stop heating/cooling (Temperature Module, Thermocycler block and
lid, Heater-Shaker heater), stop shaking, and lower Magnetic Module magnets. Only possible when
no run is in progress: stop the run first.

Input parameters:

- `module_ids`: Module IDs from list_modules; omit to switch off all modules

Output parameters:

- `result` (array)

### `list_protocols` (~27 tokens)

List Protocols

List protocols stored on the robot (newest last) with their analysis status and result.

Output parameters:

- `result` (array)

### `get_protocol` (~85 tokens)

Get Protocol

Show a stored protocol's analysis: whether it is ready to run, analysis errors, the deck layout it
expects (labware and modules per slot, pipettes per mount, liquids), the number of steps and the
highest module temperature / shake speed it requests. Review this with the user before start_run.

Input parameters:

- `protocol_id` (string, required): Protocol ID from list_protocols

Output parameters:

- `analysis_errors` (array): Errors from the robot's protocol analysis
- `analysis_id`
- `analysis_result`: 'ok', 'not-ok' or 'parameter-value-required'
- `analysis_status`: 'pending' or 'completed'
- `api_level`
- `command_count`: Number of steps in the analyzed protocol
- `created_at`
- `deck`: Labware, modules and pipettes the protocol expects
- `files` (array)
- `id` (string)
- `max_module_temperature_c`: Highest module temperature the protocol requests
- `max_shake_speed_rpm`: Fastest Heater-Shaker speed the protocol requests
- `message` (string)
- `name` (string)
- `problems` (array)
- `protocol_type`: 'python' or 'json'
- `ready_to_run` (boolean): True only if analysis completed with result 'ok' and limits pass
- `robot_type`
- `run_time_parameters` (array)

### `upload_protocol` (~129 tokens)

Upload Protocol

Upload a protocol file (plus optional custom labware) to the robot. The robot analyzes it
(simulates it) and this tool returns the analysis: errors, deck layout and whether it is ready
to run. Uploading does not move the robot. Uploading identical files returns the existing protocol.

Input parameters:

- `labware_paths`: Custom labware definition .json files used by a Python protocol
- `path` (string, required): Local path of the protocol file (.py Python API or .json)
- `wait_for_analysis_s` (number): How long to wait for the robot's analysis to finish

Output parameters:

- `analysis_errors` (array): Errors from the robot's protocol analysis
- `analysis_id`
- `analysis_result`: 'ok', 'not-ok' or 'parameter-value-required'
- `analysis_status`: 'pending' or 'completed'
- `api_level`
- `command_count`: Number of steps in the analyzed protocol
- `created_at`
- `deck`: Labware, modules and pipettes the protocol expects
- `files` (array)
- `id` (string)
- `max_module_temperature_c`: Highest module temperature the protocol requests
- `max_shake_speed_rpm`: Fastest Heater-Shaker speed the protocol requests
- `message` (string)
- `name` (string)
- `problems` (array)
- `protocol_type`: 'python' or 'json'
- `ready_to_run` (boolean): True only if analysis completed with result 'ok' and limits pass
- `robot_type`
- `run_time_parameters` (array)

### `list_runs` (~31 tokens)

List Runs

List recent protocol runs, newest first, with their status.

Input parameters:

- `limit` (integer): Maximum runs to list

Output parameters:

- `result` (array)

### `get_run_status` (~78 tokens)

Get Run Status

Report a run's status, the step it is on, progress, recent steps and any errors, plus advice on
what to do next (e.g. when the run is waiting for error recovery).

Input parameters:

- `recent_commands` (integer): How many recent steps to include
- `run_id`: Run ID; omit for the current run

Output parameters:

- `advice` (string)
- `commands_executed` (integer): Commands queued or run so far
- `commands_expected`: Commands in the protocol analysis
- `completed_at`
- `created_at`
- `current` (boolean)
- `current_command`
- `errors` (array)
- `id` (string)
- `progress_percent`
- `protocol_id`
- `recent_commands` (array)
- `recovering_from`
- `started_at`
- `status` (string): idle, running, paused, blocked-by-open-door, stop-requested, finishing, awaiting-recovery(-paused/-blocked-by-open-door), stopped, failed, succeeded
- `timestamp` (string)

### `start_run` (~124 tokens)

Start Run

Create a run of an analyzed protocol and start it: the robot begins moving and pipetting.
Refused unless the protocol's analysis completed without errors, its module setpoints are within
the safety limits, no other run is active, the door is closed and the E-stop is released.

Input parameters:

- `deck_confirmed` (boolean, required): True only after the user confirmed the deck matches get_protocol's layout (labware, tips, liquids, modules) and nothing else is in the robot's path
- `protocol_id` (string, required): Protocol ID from upload_protocol or list_protocols

Output parameters:

- `advice` (string)
- `commands_executed` (integer): Commands queued or run so far
- `commands_expected`: Commands in the protocol analysis
- `completed_at`
- `created_at`
- `current` (boolean)
- `current_command`
- `errors` (array)
- `id` (string)
- `progress_percent`
- `protocol_id`
- `recent_commands` (array)
- `recovering_from`
- `started_at`
- `status` (string): idle, running, paused, blocked-by-open-door, stop-requested, finishing, awaiting-recovery(-paused/-blocked-by-open-door), stopped, failed, succeeded
- `timestamp` (string)

### `pause_run` (~44 tokens)

Pause Run

Pause a running protocol. The robot finishes its current step and then holds; resume_run
continues it.

Input parameters:

- `run_id`: Run ID; omit for the current run

Output parameters:

- `accepted` (boolean)
- `action` (string)
- `message` (string)
- `run_id`
- `status`
- `timestamp` (string)

### `stop_run` (~57 tokens)

Stop Run

Stop (cancel) a run immediately. A stopped run cannot be resumed; the robot homes and drops
any attached tips into the trash. Use this whenever something looks wrong.

Input parameters:

- `run_id`: Run ID; omit for the current run

Output parameters:

- `accepted` (boolean)
- `action` (string)
- `message` (string)
- `run_id`
- `status`
- `timestamp` (string)

### `resume_run` (~124 tokens)

Resume Run

Resume a paused run (the robot starts moving again), or leave error recovery. Refused while the
door is open. For a run awaiting recovery, `error_recovery` must be given.

Input parameters:

- `error_recovery`: Only for runs awaiting error recovery, after the user physically checked the robot: 'continue' resumes from the robot's current state (the failed step is skipped); 'assume_false_positive' treats the…
- `run_id`: Run ID; omit for the current run

Output parameters:

- `advice` (string)
- `commands_executed` (integer): Commands queued or run so far
- `commands_expected`: Commands in the protocol analysis
- `completed_at`
- `created_at`
- `current` (boolean)
- `current_command`
- `errors` (array)
- `id` (string)
- `progress_percent`
- `protocol_id`
- `recent_commands` (array)
- `recovering_from`
- `started_at`
- `status` (string): idle, running, paused, blocked-by-open-door, stop-requested, finishing, awaiting-recovery(-paused/-blocked-by-open-door), stopped, failed, succeeded
- `timestamp` (string)

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/k-dense-ai-labmcp-opentrons/labmcp-opentrons#diagnostics

## Score history

- 2026-09-30: 70
- 2026-09-29: 70
- 2026-09-28: 69
- 2026-09-27: 40
- 2026-09-26: 40
- 2026-09-25: 73

## Common questions

### What is the Opentrons OT-2 / Flex MCP server?

Opentrons OT-2 / Flex is an MCP server listed in the public MCP registry as io.github.K-Dense-AI/labmcp-opentrons. MCP server for Opentrons OT-2 and Flex liquid-handling robots (HTTP API). This page covers its PyPI package (labmcp-opentrons).

### Is the Opentrons OT-2 / Flex MCP server safe to use?

Opentrons OT-2 / Flex scores 70 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 30 September 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Opentrons OT-2 / Flex MCP server expose?

Opentrons OT-2 / Flex exposes 18 tools: get_connection_info, get_command_log, reconnect, get_robot_status, list_instruments, and 13 more. Their descriptions and schemas cost roughly 1,122 tokens of context every time the server is loaded.

### Is the Opentrons OT-2 / Flex MCP server still maintained?

Opentrons OT-2 / Flex is still listed as active in the MCP registry. We last reached this channel on 30 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the Opentrons OT-2 / Flex MCP server under?

Opentrons OT-2 / Flex declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- PyPI project: https://pypi.org/project/labmcp-opentrons/
- Socket report: https://socket.dev/pypi/package/labmcp-opentrons
- Repository: https://github.com/K-Dense-AI/lab-instrument-mcps
- Website: https://github.com/K-Dense-AI/lab-instrument-mcps/tree/main/servers/biology/opentrons
- Changelog RSS feed: https://verifymcp.io/servers/k-dense-ai-labmcp-opentrons/labmcp-opentrons.xml
- Changelog JSON feed: https://verifymcp.io/servers/k-dense-ai-labmcp-opentrons/labmcp-opentrons.json
- HTML version of this page: https://verifymcp.io/servers/k-dense-ai-labmcp-opentrons/labmcp-opentrons