This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Control PyMOL from Cursor via the Model Context Protocol (MCP). Describe structures and styles in plain language; the assistant calls PyMOL through XML‑RPC (run_command, run_python, pymol_get).
This project packages and documents a Cursor-first workflow. The same MCP server works with Claude Code if you prefer that CLI.
Upstream inspiration: nagarh/pymol-claude-code (PyMOL + MCP for Claude Code). This repo extends that idea with portable Cursor config, checks, scripts, and install docs.
Same diagram style as upstream flow.svg, updated for Cursor (cyan node). Uses SVG/CSS animation (animateMotion, keyframes). If your Markdown preview looks static, open flow.svg directly on GitHub for the full motion.
Related MCP server: vmd-mcp
Piece | Purpose |
| MCP server (stdio) → PyMOL XML‑RPC |
| Registers the |
| Agent hints for PyMOL tool usage |
| Launch PyMOL with |
| Sanity check: venv + MCP import + RPC to PyMOL |
| Example PyMOL script (labels / pocket) |
| Animated architecture diagram (same style as upstream repo) |
git clone https://github.com/truong128/pymol-cursor-mcp.git
cd pymol-cursor-mcp
python3 -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -U pip
pip install -r requirements.txt
deactivateInstall PyMOL (conda‑forge recommended), then start RPC:
conda activate pymol_mcp # your env with pymol-open-source
pymol -ROr: ./scripts/start_pymol_for_mcp.sh (after chmod +x).
In Cursor: Open Folder → this repo → Settings → MCP → confirm pymol connected → restart Cursor if needed.
python3 verify_stack.pyShould print: OK: MCP import + PyMOL RPC at http://localhost:9123
Full step-by-step: INSTALL.md
Terminal: pymol -R or VS Code/Cursor task: “PyMOL: start with XML-RPC”.
Cursor: Chat / Agent with this folder open.
Prompt: e.g. “Fetch 1hvr, cartoon on protein, sticks on ligand.”
Topic | Here |
IDE | Cursor primary; |
RPC URL |
|
Paths |
|
Windows |
|
Verify |
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PyMOL start |
|
MCP disconnected: see Cursor Output → MCP Logs; recreate venv; reopen repo root as workspace.
PyMOL errors / missing .dylib: install PyMOL from conda-forge into a dedicated env (see INSTALL.md).
Remote/HPC: run MCP where your editor runs; tunnel RPC (PYMOL_RPC_URL, SSH -R) — details in INSTALL.md.
PyMOL MCP idea and original server: pymol-claude-code — Hemant Nagar.
Packaging and Cursor-focused docs: truong128. - Truong Nguyen
MIT — see LICENSE.
Use your Mac, Windows or Linux computer from ChatGPT, Claude or Codex: files, commands, documents.
Connect ChatGPT, Claude, Cursor or VS Code to your Windows PC: files, terminal, browser, apps.
Run, debug, and triage tests from your IDE using natural language, no dashboard switching, no manual data transfers. The TestMu AI (formerly LambdaTest) MCP Server is a single remote server exposing four tool suites: HyperExecute — analyze your project, generate YAML configs and test runner commands, then monitor jobs and sessions. Automation — pull a TestID's details plus command, network, and console logs into one chat for instant root-cause analysis. Includes mobile app upload. SmartUI — explain pixel, layout, DOM, and perceptual changes in a visual regression run, with context-aware React/HTML/CSS fixes. Accessibility — audit any public URL or a local React app against WCAG and get ready-to-apply remediation steps. Connects over https://mcp.lambdatest.com/mcp using OAuth 2.1 — no API keys in your config. One-click install in Cursor; works with Claude, GitHub Copilot, Cline, and any MCP client. Tests execute on the TestMu AI cloud: 3,000+ browsers and 10,000+ real devices.
Give your AI hands on every computer you own. Remote control of your Windows, Mac and Linux machines from one ChatGPT, Claude or Cursor chat — even from your phone. Ask it to find out why the office server is crawling, update every PC in the house, sort out your mom's laptop from another city, or ship the site from your work machine while you're on a train. It runs commands, reads files and takes a screenshot when it needs to see the screen. You decide what each computer allows, and you can cut any of them off in a second.
