agentmods.dev

cell-classify

cell-classify is an MCP server for Claude Code, Codex, Cursor, Gemini CLI, OpenCode from lynnlangit/precision-medicine-mcp. Its token cost is not measured, scanned A, original, Apache-2.0.

A local MCP server configuration for a Python package named cell-classify. The name suggests cell classification, but the provided configuration does not document the server’s actual operations.

In plain words
What is it for?
Use it to start the cell-classify server locally, set its output directory, and keep it in dry-run mode. The input does not support more specific job descriptions.
Why use it?
It gives an MCP client a defined local startup command and specifies where output should go. Its dry-run setting can be enabled without assuming the server’s detailed behavior.

MCP server for Claude CodeCodexCursorGemini CLIOpenCode

Written for no agent in particular: it speaks MCP, so any client can run it. Also seen: listed in a Claude config.

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/lynnlangit/Documents/GitHub/spatial-mcp/servers/mcp-cell-classify.

One of 19 entries in claude_desktop_config.json upstream. Installing this one merges just its entry into your config; the other 18 are separate, each on its own page.

not rated 24repo 16d ago A scan tokens not measured original Apache-2.0

Good fit Use it to start the cell-classify server locally, set its output directory, and keep it in dry-run mode. The input does not support more specific job descriptions.

Compare 6 mcp servers from other repositories ↓
View source ↗ lynnlangit/precision-medicine-mcp
Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

Made for: Claude Code, Codex, Cursor, Gemini CLI, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for cell-classify

README.md
[![agentmods](https://agentmods.dev/badge/mcp/lynnlangit/precision-medicine-mcp/desktop-configs-cell-classify/github.svg)](https://agentmods.dev/mcp/lynnlangit/precision-medicine-mcp/desktop-configs-cell-classify)
Your own site
<a href="https://agentmods.dev/mcp/lynnlangit/precision-medicine-mcp/desktop-configs-cell-classify"><img src="https://agentmods.dev/badge/mcp/lynnlangit/precision-medicine-mcp/desktop-configs-cell-classify/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for cell-classify

Your own site · 80×15
<a href="https://agentmods.dev/mcp/lynnlangit/precision-medicine-mcp/desktop-configs-cell-classify"><img src="https://agentmods.dev/badge/mcp/lynnlangit/precision-medicine-mcp/desktop-configs-cell-classify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session not measured What this adds to a session before it is invoked.
When invoked not measured Not applicable: nothing here is loaded into a session.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Security

Grade A, and why

cell-classify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

docs/getting-started/desktop-configs/claude_desktop_config.json · 17 lines

What it actually says

{
  "cell-classify": {
    "command": "uv",
    "args": [
      "run",
      "--directory",
      "/Users/lynnlangit/Documents/GitHub/spatial-mcp/servers/mcp-cell-classify",
      "python",
      "-m",
      "mcp_cell_classify"
    ],
    "env": {
      "CELL_CLASSIFY_OUTPUT_DIR": "/Users/lynnlangit/Documents/GitHub/spatial-mcp/data/output",
      "CELL_CLASSIFY_DRY_RUN": "true"
    }
  }
}
Same file

What else claude_desktop_config.json configures

This page is one entry in a file that holds 19. Installing the file brings all of them; each is measured and scanned on its own page.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 17 lines scan A 096b5abe1e66

Subscribe to this mod's changes

cell-classify is an MCP server published in the GitHub repository lynnlangit/precision-medicine-mcp (24 stars, last pushed 16d ago), licensed Apache-2.0. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

agentic-aibioinformaticsmultiomicsprecision-medicinetranscriptomics
Related

Other mcp servers, from other repositories

academic-research-mcp-suite

A comprehensive Model Context Protocol (MCP) server suite for academic research workflow automation. Includes 6 specialized servers for complete research pipeline from question refinement to report generation. Runs locally from the academic-research-mcp-suite npm package.

sercantas/Academic-Research-MCP-Suite · not measured

osmp

OSMP MCP Server -- Agentic AI instruction encoding. 86.8% byte reduction vs JSON. Inference-free decode. Any channel. Runs locally from the osmp-mcp Python package.

Octid-io/cloudless-sky · not measured

computermate

MCP server exposing computer-use tools to LLMs. Runs locally from the @one710/computermate npm package.

one710/computermate · not measured

docs-langchain

MCP server "docs-langchain", hosted remotely at docs.langchain.com, as configured in langchain-ai/langchain.

langchain-ai/langchain · not measured

component-explorer

MCP server "component-explorer" as configured in microsoft/vscode. Launched with npm exec --no -- component-explorer mcp -p ./test/componentFixtures/component-ex.

microsoft/vscode · not measured

vscode-automation-mcp

MCP server "vscode-automation-mcp" as configured in microsoft/vscode. Launched with npm run start-stdio.

microsoft/vscode · not measured