claude mcp add alphafold-sovereign-mcp -- npx -y alphafold-sovereign-mcp
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
Star count
4 ★ · smaniches/alphafold-sovereign-mcp · read from the repository page · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 4 ★ · 7 sources · mcp
FAQ (answers come from our records)
How do I install it?
We did not find an install command for this repository (our install coverage is only about 4%). Check its README or releases page.
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository smaniches/alphafold-sovereign-mcp;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
Answering a structural-biology or variant question usually means querying many public databases by hand — AlphaFold DB, Open Targets, ClinVar, gnomAD, and more — and reconciling their formats. This server wraps those sources behind one set of MCP tool calls that run as a local process on your own machine, with no hosted service of ours in the path, no telemetry, and a local SQLite knowledge graph that never leaves your disk. In the default online mode the tools query those public upstreams directly, so the identifiers you look up are sent to them (and one, DisGeNET, needs its own free API key); set ALPHAFOLD_OFFLINE=1 to refuse outbound requests before any socket opens, so no identifier leaves the machine (the knowledge-graph tools still answer from local data; the upstream tools report their source as unavailable). "Sovereign" here means local-first — your compute and stored results stay on your machine — not that the server runs without a network. A Model Context Protocol server — an AlphaFold MCP server — that wraps AlphaFold DB and 8 other public biomedical data sources behind a set of MCP tool calls, with a conditional UniProtKB request to verify explicitly requested displayed isoforms. It is backed by a local SQLite knowledge graph with query and export tools (results can be persisted through its API; automatic per-invocation persistence is not yet wired). This is an unfunded, independent open-source project. It is not a service, not certified for any regulated use, and its outputs are research aids that should be reviewed by qualified humans before any clinical or regulatory use. **Research authorship:** Santiago Maniches (ORCID 0009-0005-6480-1987) independently directs and maintains this server and is the sole scientific author of its original research contributions. AI-assisted tools have supported coding, testing, and internal review. They are not scientific coauthors, clinical validators, or a substitute for independent evaluation. The public databases, prediction models, and existing algorithms remain credited to their sources. This project is not affiliated with, endorsed by, or sponsored by Google DeepMind or EMBL-EBI. "AlphaFold" is a trademark of its respective owner and is used here only to describe the public data (the AlphaFold DB API) that this software consumes. **Status:** Beta. Engineering-validated (100% line and branch coverage). Not yet scientifically validated by independent domain experts; not yet deployed in production. See STATUS.md and LIMITATIONS.md. --- What this is A Python MCP server that: - Wraps AlphaFold DB, MONDO, HPO, Open Targets, ClinVar, gnomAD, DisGeNET, ChEMBL, and Ensembl behind MCP tool calls. Explicit numbered isoforms may also trigger a UniProtKB sequence-and-identity check. Each call is a thin orchestration over those upstreams; the server does not add scientific judgement. - Composes upstreams into multi-source workflows: variant cross-reference reports, disease–target landscape summaries, heuristic target-druggability scoring, drug-repurposing candidate ranking, and cross-species structural-distance computation. - Ships a local SQLite knowledge graph (storage/knowledge_graph.py) with query, export, and traversal tools. It loads a curated boot seed automatically when empty (storage/seed.py, 16 entities and 15 relationships; disable with AFSMCP_DISABLE_KG_SEED=1) and can be extended by writing through the knowledge-graph API. There is no automatic per-invocation persistence: the analysis tools do not write to the store on their own. - Includes a topological-data-analysis (TDA) module that computes persistent-homology fingerprints (Betti numbers β₀, β₁, β₂) over Vietoris-Rips filtrations of Cα coordinates, and an L2-distance comparator between those fingerprint vectors. The full persistent-homology features require the optional [tda] extra (gudhi). It targets mcp-spec 2025-06-18 and runs on Python 3.10–3.13. **AlphaFold DB compatibility:** the prediction API announced modern model and sequence field names and a legacy-field sunset in June 2026. The sampled live API still exposes old aliases as of 9 October 2026. The client uses the current fields, retains legacy-response compatibility, and selects the exact requested UniProt accession when the API returns