Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Federated protein structure & annotation across experimental (PDB) and predicted (AlphaFold) models.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
MCP_LOG_LEVELDu brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://protein.caseyjhand.com/mcpÖffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"protein": {
"command": "npx",
"args": [
"-y",
"@cyanheads/protein-mcp-server"
],
"env": {
"MCP_LOG_LEVEL": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add --transport http protein https://protein.caseyjhand.com/mcpclaude mcp add protein --env MCP_LOG_LEVEL=your-value -- npx -y @cyanheads/protein-mcp-serverTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"protein": {
"url": "https://protein.caseyjhand.com/mcp"
}
}
}In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"protein": {
"command": "npx",
"args": [
"-y",
"@cyanheads/protein-mcp-server"
],
"env": {
"MCP_LOG_LEVEL": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"protein": {
"type": "http",
"url": "https://protein.caseyjhand.com/mcp"
}
}
}In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"protein": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@cyanheads/protein-mcp-server"
],
"env": {
"MCP_LOG_LEVEL": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
ChatGPT verbindet sich nur mit Servern im Internet:
https://protein.caseyjhand.com/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
MCP_LOG_LEVEL envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Tool-Namen und -Beschreibungen genau so, wie der Server sie am 6. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.
protein_search_structuresSearch experimental (PDB) and predicted (computed-model) protein structures by free text, protein sequence (triggers an mmseqs2 similarity search), and/or organism, method, resolution, and bound-ligand filters. Returns ranked hits; the experimental page is enriched with title, me
protein_get_structureFetch structures with metadata and coordinate-file URLs. source "experimental" takes PDB entry IDs, and also resolves the computed-model IDs protein_search_structures returns (AF_*/MA_*), which come back marked source "predicted" with their modelling provider; "predicted" takes U
protein_find_similarFind structurally or evolutionarily related proteins. by:"sequence" runs an RCSB mmseqs2 sequence-similarity search (synchronous; experimental PDB entries only — protein_search_structures with a sequence also reaches computed models) over a sequence — supplied directly, taken fro
protein_track_ligandsLigand discovery and binding-site analysis across the PDB. mode "find_ligand" resolves a name or formula to chemical component IDs with metadata (formula, weight, SMILES), ranked by deposition frequency — most-deposited component first, so the top hit is the most common match for
protein_compare_structuresStructurally align multiple structures (up to the configured batch cap; structures past it are returned in ignored) via the RCSB Structural Comparison service (TM-align / jFATCAT). reference:"first" aligns every structure to the first; reference:"all_pairs" computes the full pair
protein_analyze_collectionProfile the PDB into distributions and trends over an optional scoping query: counts by method, organism, or polymer composition; resolution and molecular-weight histograms; release-year timelines; and multidimensional cross-tabs (e.g. method × release_year). Aggregation runs at
protein_get_annotationsSequence and functional annotation for a protein: UniProt positional features (domains, binding and active sites, PTMs including cross-links and lipidation, topology, DNA binding, processing products such as chains and signal peptides, mutagenesis), natural variants, and InterPro
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 8. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto cyanheads bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Antwort in 188 ms (HTTP 200)
Keine Anmeldung nötig
Wir haben 7 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Beides geht: Installiere ihn auf deinem Computer oder verbinde dich mit der Cloud-Version.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.9.0) kam vor 4 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, A1RO — Irish employment tools
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
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@cyanheads/protein-mcp-server Federated protein structure & annotation across experimental (PDB) and predicted (AlphaFold) models via MCP. STDIO or Streamable HTTP. 7 Tools • 2 Resources
Public Hosted Server: https://protein.caseyjhand.com/mcp
Experimental (PDB) and predicted (AlphaFold) protein structures behind one surface. Search, fetch, align, and annotate structures and their ligands across RCSB, AlphaFold DB, 3D-Beacons, UniProt, InterPro, and Foldseek. No API key required.
| Tool | Description |
|---|---|
protein_search_structures | Search experimental and predicted structures by text, sequence, or organism/method/resolution, with optional facets |
protein_get_structure | Fetch metadata and coordinate URLs for experimental, predicted, or best-available structures |
protein_find_similar | Find sequence homologs (RCSB mmseqs2) or fold homologs (Foldseek) |
protein_track_ligands | Resolve ligands to component IDs, find structures containing one, or map its binding site |
protein_compare_structures | Align structures with TM-align or jFATCAT, against a reference or all pairs |
protein_analyze_collection | Profile the PDB as counts, histograms, timelines, and cross-tabs |
protein_get_annotations | Fetch UniProt features and variants plus InterPro domains with GO terms |
| Resource | Description |
|---|---|
pdb://{entry_id} | Experimental structure summary for a PDB entry |
af://{uniprot} | AlphaFold DB predicted-structure summary for a UniProt accession |
Both resources are also reachable through protein_get_structure, for clients that don't surface resources.
| Skill | Description |
|---|---|
protein-guide | Identifier forms each tool takes, author vs label chains, residue numbering, and the gates for best_available picks, sequence and Foldseek hits, ligand counts, and PDB profiles |
Served over MCP as skill://protein-guide/SKILL.md; it also ships in plugin installs, the .mcpb bundle, the npm package, and the Docker image.
protein_search_structures toolquery, sequence (an mmseqs2 search; min_identity / max_evalue apply only with it), organism, method, max_resolution, or ligand (an exact component ID held as a bound copy); content_type is experimental, predicted, or all (default); up to 100 hits per page (default 25) via limit / startorganism takes a scientific name, an NCBI common name, or a taxon ID, and matches that taxon plus every taxon under it; a word fragment matches nothing. method takes one of the 13 RCSB experimental methods in any letter case, or an alias (cryo-EM, cryoEM, EM, X-ray, xray, NMR for both NMR methods); anything else fails as unknown_methodsequence needs at least 10 residues; whitespace is stripped and case normalized, and an invalid one fails as invalid_sequence. Each hit names its source and an entry id you can pass to other tools, and carries organisms (a sequence hit's are the matched entity's). Sequence hits add identity, evalue, bitscore, and the aligned ranges, with queryLength at the response levelfacets (method, organism, polymer_type, resolution, release_year, molecular_weight) add a breakdown capped at PROTEIN_FACET_BUCKET_CAP buckets per dimension; facets count the filtered set, so an active organism or method filter constrains its own facetprotein_get_structure toolsource: experimental (default) takes PDB entry IDs and the AF_* / MA_* computed-model IDs search returns (these come back as source: predicted); predicted takes UniProt accessions, isoform accessions (P04637-2), or AlphaFold DB entry IDs (AF-P04637-2-F1) for AlphaFold models with pLDDT/PAE; best_available takes the same identifiers (an entry ID reduces to its accession) and returns the PDB entry with the widest UniProt coverage (ties to the finest resolution), else the model with the highest confidence on the lDDT scale. Best-available records carry coverage, uniprotStart, and uniprotEnd; a pick can come from a non-PDB provider, and only a record with pdbId is a PDB entry. If the PDB check is unavailable, the pick ranks the federated models alone and notice says sonotice; a demerged or deleted one lands in failed[] with its replacementsPROTEIN_MAX_BATCH_IDS are looked up per call (default 25) and the remainder comes back in ignored. One 50 s budget covers all upstream lookups in a call; under predicted and best_available, an ID it stops, or whose upstream lookup fails (an error status, an HTML page, a network failure), lands in failed[] with a reason to re-call itfailed[]; when nothing resolves the call fails as upstream_unavailable (retryable, with data.failed) if every ID's lookup failed upstream or ran out of the 50 s budget, so none is known to lack a structure, and otherwise as all_failed (with data.failed); it fails mixed_id_types when the IDs don't fit source. Records include coordinateUrls for the files that exist, and organisms under experimental and predictedinclude_coords inlines coordinate text in 24,000-character windows: a single selected structure pages with coords_offset, passing back coordinatesNextOffset until it is absent; several selected files inline whole only when together they fit one window, otherwise an overflow outline lists each file's length to re-call with sections: [id]. coords_offset above 0 needs exactly one selected structure (coords_offset_needs_one_structure)protein_find_similar toolby: sequence runs a synchronous RCSB mmseqs2 search over experimental PDB entries only (protein_search_structures with a sequence also reaches computed models) from sequence, pdb_id, or uniprot, filtered by max_evalue / min_identity; by: structure runs an async Foldseek search from pdb_id (its mmCIF file) or uniprot (its AlphaFold DB model) against pdb100 + afdb50 unless databases says otherwise. uniprot takes a canonical or isoform accession, or a UniProtKB entry name such as HBA_HUMAN (resolved to its entry's accession), in both modes and is shape-checked before any request (invalid_accession). databases takes exactly these case-sensitive names: pdb100, afdb50, afdb-swissprot, afdb-proteome, bfvd_v3, cath50, mgnify_esm30, gmgcl_id, bfmd; any other fails schema validation (-32602), and a name Foldseek itself refuses fails as databases_rejected. A field only the other mode reads fails as mode_mismatched_field; up to 100 hits per page (default 25)protein_search_structures, and a direct sequence wins over identifiers. A pdb_id sequence query searches one protein entity: the one holding chain (author chain, case-sensitive, by: sequence only, requires pdb_id), else the lowest-numbered protein entity of at least 10 residues; DNA and RNA entities are never searched. The response names it in queryEntityId, and a notice lists the entry's other protein entities. An unmatched chain fails as chain_not_found, and chain without pdb_id as chain_without_pdb_idsource (and database for structure hits), ranked by score; sequence hits add identity, evalue, bitscore, and the aligned ranges. Responses report totalCount, nextStart, and queryLengthuniprot accession answers for its successor with a notice; a demerged or deleted one fails as inactive_accession with its replacements. A by: structure coordinate file is limited to 16,000,000 characters, and a larger one fails as structure_too_largetarget name and an id only when the target resolves to a PDB entry or UniProt accession; bfvd_v3, mgnify_esm30, gmgcl_id, and bfmd hits have none. Other structure-hit fields: chain (a -N suffix marks a symmetry copy), title, probability, organisms / taxId (the target's, where Foldseek classifies it), and the aligned spans queryStart, queryEnd, targetStart, targetEnd, targetLength. A sequence hit's organisms are the matched entity'sstatus: computing with a ticketId; re-call with ticket_id to resume it. A job Foldseek accepted before the call's 50 s budget ran out comes back the same way. For a new search the poll window starts when the call does, so identifier lookups and the coordinate download come out of it. A multichain structure is searched one chain at a time via query (0-based, default 0) out of queryCountprotein_track_ligands toolmode is find_ligand (query: a name or formula), structures_with_ligand (comp_id), or binding_site (pdb_id, optional comp_id); a missing mode input fails as missing_param. limit is 1–100 (default 25), and start pages the last two modesfind_ligand returns component IDs with formula, weight, SMILES, and InChIKey, ranked by depositionCount, with totalCount and candidatesConsidered showing when the candidate pool was cut short; structures_with_ligand lists entries highest resolution first, each with title, method, and hostEntities (the polymer entities whose chains the depositor assigned the ligand to)depositionCount equals the totalCount of structures_with_ligand for the same componentbinding_site returns pocketNur der Anfang wird gezeigt; den Rest findest du im Repo