Squidpy Remote Tool (MCP Server)#

TOU validation and deployment status (2026-08-16)#

Squidpy dependencies, loopback discovery, and a bounded 72-spot neighborhood-enrichment call passed with a finite 3 x 3 z-score matrix. Public publication, cross-user isolation, representative spatial biology, broad concurrency, and recovery remain incomplete. Authenticated private Platform import and owner testing passed on 2026-08-16; public publication and independent-caller authorization/isolation remain untested.

  • Operation: run_squidpy_nhood_enrichment

  • Start: python -m tooluniverse.remote.squidpy.squidpy_tool

  • Endpoint: http://127.0.0.1:8016/mcp

  • Provider configuration: set TOOLUNIVERSE_REMOTE_DATA_ROOT; approved H5AD inputs need valid spatial coordinates and cluster_key.

  • TOU check: tu doctor --forward http://127.0.0.1:8016/mcp --json

  • Private relay: tu serve --share --forward http://127.0.0.1:8016/mcp --name validation-squidpy --workers 1

Non-loopback binding requires TOOLUNIVERSE_API_TOKEN; otherwise keep the server on loopback. The relay requires TOOLUNIVERSE_SERVICE_KEY. Public publication and independent-caller testing were not run.

New-user check: python scripts/remote_validation/setup_skill_preflight.py --implementation squidpy. Add --check-provider-env before launch, --live after launch, and --check-connect-prereqs before sharing. Live preflight checks exact MCP discovery only; it does not run or validate a model. The pinned relay SDK is not on PyPI and currently requires authorized GitHub repository access plus a configured SSH key, so a working local MCP server does not by itself prove that a new operator can share it.

The authenticated 2026-08-16 Platform matrix found all 30 private owner relays online and all 41 operations discoverable. This implementation was imported as unpublished owner draft(s), configured with a 120-second timeout, and invoked through /expert-sessions/{id}/test. 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.

See the complete setup and verification guide.

Serves Squidpy (Palla et al., Nature Methods 2022) — spatial single-cell omics analysis — as a ToolUniverse remote tool: run_squidpy_nhood_enrichment, which builds a spatial neighbors graph and runs the neighborhood-enrichment permutation test (which cell-type pairs co-localize vs. segregate).

Served remotely (not bundled) because squidpy pulls in scanpy/anndata + networkx + scikit-image + numba.

Authorize once, then share with one short command#

After installing this provider’s dependencies and the pinned Connect relay SDK, and exporting its required resources, run 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:

tu remote share squidpy

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 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 selects the reviewed environment, checks it, starts or reuses the exact loopback MCP tool set, runs the TU Platform preflight, and keeps the private relay in the foreground until Ctrl-C. Override defaults only when needed:

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

Use tu remote run squidpy for local-only operation. Sharing does not publish a tool or prove scientific accuracy.

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 locally stored key.

Deploy#

pip install -r requirements.txt          # squidpy + scanpy + anndata
python squidpy_tool.py                     # starts the MCP server on 127.0.0.1:8016

Inputs are referenced by adata_path (a server-accessible spatial .h5ad with adata.obsm["spatial"] coordinates and the cluster_key column in adata.obs), since spatial matrices are large. Expose remotely only behind TOOLUNIVERSE_API_TOKEN (SMCP bind guard).

Register in ToolUniverse#

Tool definitions: src/tooluniverse/data/remote_tools/squidpy_tools.json (type: RemoteTool). Connect via the standard MCPAutoLoaderTool/server_url mechanism.