Cmxflow
Run composable cheminformatics pipelines—ligand prep, clustering, virtual screens—from your agent via cmxflow MCP.
Overview
cmxflow is an MCP server for the Build phase that runs composable cheminformatics workflows such as ligand prep, clustering, and virtual screening from your agent.
What is this MCP server?
- Composable, tunable cheminformatics workflows: prepare ligands, cluster, virtual screens, and related steps
- PyPI cmxflow via uvx runtime hint (cmxflow-mcp entry) v0.3.1 stdio MCP
- Documented project site at b-shields.github.io/cmxflow for workflow reference
- Agent-driven pipeline orchestration instead of manual CLI chaining for each study
- Scientific compute integration—not a generic CRUD or marketing MCP
- PyPI package cmxflow version 0.3.1 with cmxflow-mcp stdio entry
- Documented websiteUrl https://b-shields.github.io/cmxflow/
- GitHub repository b-shields/cmxflow
Community signal: 1 GitHub stars.
What problem does it solve?
Cheminformatics pipelines are brittle chains of CLI steps that are painful to rerun, tune, and explain from a coding agent.
Who is it for?
Builders of chem/bio tools or internal R&D automation who already work in cheminformatics and use MCP-capable agents.
Skip if: Typical indie app or content founders with no molecular modeling or virtual screening requirements.
What do I get? / Deliverables
After setup, your agent can trigger structured cmxflow workflows for preparation, clustering, and screening without hand-rolling each command sequence.
- Agent-triggered ligand prep, clustering, and screening workflows
- Repeatable tunable pipelines without manual CLI scripting each run
- Integration hook for chemistry-focused build products
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Journey fit
Build integrations is where specialized scientific tooling plugs into agent workflows; cmxflow is not a general launch or grow utility. Virtual screening and ligand preparation are domain pipelines you wire in during product build for chem/bio R&D tools.
How it compares
Domain cheminformatics MCP, not a general database or cloud deploy server.
Common Questions / FAQ
Who is Cmxflow MCP for?
Developers and researchers building chemistry-aware products who want agents to orchestrate Cmxflow pipelines.
When should I use Cmxflow MCP?
Use during build when integrating ligand prep, clustering, or virtual screening into an agent-assisted R&D or product workflow.
How do I add Cmxflow to my agent?
Configure stdio MCP with the PyPI uvx path for Cmxflow (Cmxflow-mcp), per registry runtimeArguments, then connect your client.