Set up CellTypist as a remote tool

SkillCloud & infra

Set up, launch, validate, and troubleshoot the CellTypist ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Set up CellTypist as a remote tool skill

What this skill tells your AI

The instructions your AI receives, as published by mims-harvard/tooluniverse in skills/setup-celltypist-remote-tool/SKILL.md and read by ahel’s review.

Validation status (2026-08-16): working CPU deployment. The live MCP call annotated 80 cells from the official CellTypist sample and completed majority voting. A converted data-only model produced the same 80 labels and probabilities as the digest-pinned upstream model (maximum probability delta 0.0). This is runtime equivalence evidence, not an annotation-accuracy benchmark. Authenticated private Platform import and owner testing passed on 2026-08-16; public publication and independent-caller authorization/isolation remain untested.

Prerequisites

  • Run from the ToolUniverse repository root on Linux with Python 3.12.3.
  • CPU is sufficient for the validated model and sample.
  • Keep provider data, weights, caches, and credentials outside Git.
  • Bind to loopback. A non-loopback bind requires TOOLUNIVERSE_API_TOKEN; never put it in arguments or results.

Run the standard-library contract check before downloading large dependencies:

python scripts/remote_validation/setup_skill_preflight.py --implementation celltypist

After exporting provider resources, add --check-provider-env. After the server starts, add --live to verify the exact MCP tool set without running the model. Before sharing, add --check-connect-prereqs; this reports only whether a key is set and never prints its value.

Create an isolated environment

python3 -m venv .venvs/celltypist
. .venvs/celltypist/bin/activate
python -m pip install --upgrade pip
python -m pip install -e .
python -m pip install -r src/tooluniverse/remote/celltypist/requirements.txt

Package/network-dependent commands must be rerun in a clean environment before marking this skill complete.

Obtain data and provision a safe model

  • Set TOOLUNIVERSE_REMOTE_DATA_ROOT to the provider-owned directory containing normalized .h5ad inputs.
  • Download the model only from the official CellTypist host and verify its digest independently. The validated Immune_All_Low.pkl v2 digest is 290874d35dac039d4c9218c343fde4aac1077709b72a331ce7266f6828c36502.
  • In an isolated provisioning environment only, convert the reviewed pickle into a data-only archive:
python src/tooluniverse/remote/celltypist/convert_pickle_model.py \
  caches/celltypist/source/Immune_All_Low.pkl \
  caches/celltypist/safe-models/Immune_All_Low.npz \
  --expected-sha256 290874d35dac039d4c9218c343fde4aac1077709b72a331ce7266f6828c36502
export CELLTYPIST_SAFE_MODEL_DIR="$PWD/caches/celltypist/safe-models"

The remotely callable server must never invoke the converter, Model.load, or model download helpers. It opens only the data-only NPZ with allow_pickle=False.

Authorize once, then share with one short command

After installing dependencies, exporting the provider resources above, and installing the pinned relay SDK described under Connect below, run from the repository root. Log in only once per machine (and again after key rotation):

tu remote login
# Or import an existing protected 0600 file without sourcing it:
tu remote login --env-file /path/to/tooluniverse-service.env

Then each private share is one short command:

tu remote share celltypist

By default, tu remote login requests a short-lived device code, opens the TU Platform approval page, and polls until the signed-in user approves. No key copy/paste is required. On a headless machine, add --no-browser and open the printed link elsewhere. The CLI exchanges the approval for a computer-only key, verifies /remote-servers/preflight, stores it in a local 0600 config file, and never displays it.

The share command runs environment and TU Platform preflights, starts or reuses the exact loopback endpoint, validates discovery, and keeps the relay in the foreground until Ctrl-C. It automatically uses the reviewed Python, name, and worker count. Override them only when needed:

tu remote share celltypist --name my-celltypist-remote --workers 1

Use tu remote check celltypist for a non-sharing readiness check and tu remote run celltypist for a local-only foreground server.

In an interactive terminal, sharing automatically starts the same browser flow when the key is missing, expired, or revoked. A malformed or revoked explicit TOOLUNIVERSE_SERVICE_KEY fails fast instead of being silently replaced; unset or correct it, then run tu remote login. Non-interactive jobs also fail fast. Use tu remote logout to remove only the local copy. Use tu remote logout --revoke to revoke the computer-only platform connection first; the server record remains offline for owner inspection.

Start and verify locally

mkdir -p caches/celltypist runs/celltypist/runtime/celltypist \
  runs/celltypist/runtime/matplotlib runs/celltypist/runtime/cache
export CELLTYPIST_SAFE_MODEL_DIR="$PWD/caches/celltypist/safe-models"
export CELLTYPIST_FOLDER="$PWD/runs/celltypist/runtime/celltypist"
export MPLCONFIGDIR="$PWD/runs/celltypist/runtime/matplotlib"
export TOOLUNIVERSE_CACHE_DIR="$PWD/runs/celltypist/runtime/cache"
python -m tooluniverse.remote.celltypist.celltypist_tool

The runtime directories must be writable by the service account. CellTypist, Matplotlib, and ToolUniverse otherwise default to home-directory caches, which break startup or persistence when the deployment has a read-only home.

The Streamable HTTP endpoint is http://127.0.0.1:8014/mcp. In a second activated shell run:

python - <<'PY'
import asyncio
from fastmcp import Client

async def main():
    async with Client("http://127.0.0.1:8014/mcp") as client:
        print([tool.name for tool in await client.list_tools()])

asyncio.run(main())
PY

Confirm discovery contains run_celltypist_annotate; stop on empty, duplicate, or schema-drifted discovery.

Connect to ToolUniverse Connect

The tuplatform-connect relay is not yet published on PyPI. Install the reviewed public wheel below; its SHA-256 is pinned. Interactive sharing uses browser device authorization, so no key copy/paste or GitHub access is required.

python -m pip install fastmcp pyyaml "tuplatform-connect @ https://connect.aiscientist.tools/downloads/tuplatform_connect-0.3.0-py3-none-any.whl#sha256=3fad5eee5ecf7887a693d93ccd1aa112dc0955617a885d1fc3daded0030f9ae0"
tu doctor --forward http://127.0.0.1:8014/mcp --json
tu serve --share --forward http://127.0.0.1:8014/mcp --name validation-celltypist --workers 1

Prefer browser device authorization. For CI or migration, supply TOOLUNIVERSE_SERVICE_KEY only through a protected environment or use tu remote login --manual-key; never put a key in shell arguments.

The authenticated 2026-08-16 Platform matrix found all 30 private owner relays online and all 41 operations discoverable. All imports remained unpublished owner drafts and were invoked through /expert-sessions/{id}/test. This implementation's draft(s) used a 120-second timeout and remote max concurrency 1.

Across the set, 38 unique operations passed return-schema and semantic validation; the three USPTO operations returned exact provider HTTP 403 and remain credential-blocked. Public publication, independent-caller authorization/isolation, broad saturation, and persistent supervision were not tested.

Run a verified example

Operation: run_celltypist_annotate

{"adata_path":"celltypist_official_sample_80.h5ad","model":"Immune_All_Low.pkl","majority_voting":true}

Invoke the example through the live local MCP endpoint:

python - <<'PY'
import asyncio
import json
from fastmcp import Client

async def main():
    arguments = json.loads('''{"adata_path":"celltypist_official_sample_80.h5ad","model":"Immune_All_Low.pkl","majority_voting":true}''')
    async with Client("http://127.0.0.1:8014/mcp") as client:
        result = await client.call_tool("run_celltypist_annotate", arguments)
        print(result)

asyncio.run(main())
PY

Expected success shape: artifact_format=celltypist-safe-npz-v1, the pinned source_sha256, n_cells, aligned cell_ids/predicted_labels, and label_counts summing to n_cells. The validated call returned 80 labels with majority_voting=true. Check scientific meaning, output bounds, invalid-input behavior, and absence of paths, secrets, and traces; no biological-accuracy claim follows from a successful run.

Tune GPU and concurrency

  • Use one worker as a conservative, unmeasured default.
  • Measure cold start, two warm calls, then parallel levels 1, 2, 4, 8, and only 16 if memory permits.
  • Record successes/errors, p50/p95, peak RAM/VRAM, utilization, queueing, cancellation cleanup, and recovery.
  • Increase workers only after single-flight initialization and sanitized recoverable OOM/timeout behavior are proven.

Troubleshoot and clean up

  • Import/executable failure: reactivate the isolated environment and reinstall its requirements.
  • Read-only home/cache failure: verify CELLTYPIST_FOLDER, MPLCONFIGDIR, and TOOLUNIVERSE_CACHE_DIR all name writable provider directories.
  • Missing artifact: inspect provider-only environment variables and approved relative files; never accept arbitrary caller model paths.
  • 401/403 on deliberate network binding: configure matching TOOLUNIVERSE_API_TOKEN bearer auth; prefer loopback plus relay.
  • Stop server/relay with Ctrl-C. If installed, run tuplatform-service uninstall --name validation-celltypist.
  • Revoke temporary keys. After confirmation, remove only .venvs/celltypist, caches/celltypist, and runs/celltypist; never use a broad recursive target.

Use only official upstream documentation linked by the implementation README; do not substitute third-party model mirrors.

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Sep 2026
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Source
github.com/mims-harvard/tooluniverse