Spectrum-level proteomics scoring tools exposed through CLI and MCP
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# proteomics-mcp [](https://github.com/UadKLab/proteomics-mcp/actions/workflows/tests.yml) [](https://www.python.org/downloads/) [](https://github.com/UadKLab/proteomics-mcp/blob/main/LICENSE) [](https://modelcontextprotocol.io/) <p align="center"> <img src="https://raw.githubusercontent.com/UadKLab/proteomics-mcp/main/icon.svg" alt="Proteomics MCP" width="540"> </p> `proteomics-mcp` is a local-first MCP server and Python package for inspecting proteomics identification results and interrogating selected MS2 spectra. It turns heterogeneous de novo and search-engine outputs into one usable workflow: inspect IDs and peptides, retrieve the relevant spectrum, predict fragments, score the candidate, annotate the observed signal, and render an interactive report. Interactive HTML reports load Plotly from a CDN when opened; see the [privacy policy](https://github.com/UadKLab/proteomics-mcp/blob/main/PRIVACY.md). ## What It Supports - Input adapters for InstaNovo, Casanovo, MaxQuant, FragPipe, Proteome Discoverer, and user-mapped tables. - Modified peptidoforms normalized to inline UNIMOD notation, such as `C[UNIMOD:4]` and `M[UNIMOD:35]`. - Local IPC/Feather spectra, mzML, MGF, Bruker `.d`, and USI retrieval. - Local MS2PIP and remote Koina/Prosit fragment prediction. - On-demand spectrum scoring, observed-spectrum annotation, three interactive HTML views, and publication-ready static SVG/PDF/PNG spectrum figures. - PSM/peptide tables, structured dataset summaries, dashboards, SDRF context, and resumable batch prediction/scoring artifacts. The package does not run local InstaNovo inference, perform FDR/q-value analysis, or carry out protein inference. ## Quick Start Install from [PyPI]…
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