Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
MCP server to search, inspect, and cross-reference RCSB Protein Data Bank structures
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.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"rcsb": {
"command": "uvx",
"args": [
"rcsb-mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add rcsb -- uvx rcsb-mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"rcsb": {
"command": "uvx",
"args": [
"rcsb-mcp"
]
}
}
}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": {
"rcsb": {
"type": "stdio",
"command": "uvx",
"args": [
"rcsb-mcp"
]
}
}
}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.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto rcsb bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 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.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.23.0) kam vor 14 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
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
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Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
An MCP server for interrogating Protein Data Bank structures — discover, inspect, and cross-reference — from LLM clients (Claude Desktop, MCP Inspector, Cursor, etc.). It spans three RCSB APIs:
Searching is two steps: build a query with an rcsb_query_* tool, then execute it with rcsb_search_request. The builders are pure — they return a query document (readable JSON plus a digest) and touch no network, so nothing is searched until you call `rcsb_search_request`. rcsb_query_composer joins two or more documents with AND/OR, which is also how a single search mixes services (e.g. sequence similarity AND an organism filter).
Build
| Tool | What it does |
|---|---|
rcsb_query_fulltext | Free-text keyword query (e.g. "CRISPR Cas9"). |
rcsb_query_attribute | Structured query on one or more indexed attributes (resolution, organism, release date, ...) joined by a single logical_operator. Each condition supports exists, negation, case_sensitive; chemical_attributes=True selects the chemical-component catalog. |
rcsb_query_sequence | MMseqs2 sequence-similarity query (BLAST-like), with identity / e-value cutoffs. |
rcsb_query_chemical | Chemical query by SMILES/InChI descriptor (whole-molecule or substructure) or molecular formula. |
rcsb_query_structure | 3D shape-similarity query against a reference PDB assembly or chain. |
rcsb_query_seqmotif | Short sequence-motif query (PROSITE pattern, regex, or simple wildcards). |
rcsb_query_strucmotif | 3D structural-motif query: a geometric arrangement of specific residues (e.g. a catalytic triad). |
rcsb_query_composer | Join 2+ query documents with AND/OR — nested boolean logic, and the only way to combine different services in one search. |
Run
| Tool | What it does |
|---|---|
rcsb_search_request | Execute a query document and return matching identifiers only. Carries every output option: return_type, limit/offset, all_hits, facets, sort_by/sort_direction, group_by/group_by_ranking, include_computed_models. |
Discover
| Tool | What it does |
|---|---|
rcsb_list_pdb_search_attributes | Discover searchable attribute paths, types, and operators. schema="structure" (default, ~636) or schema="chemical" (~58: chem_comp.*, drugbank_info.*, ...). Records also carry enum (closed value sets) and nested_group (attributes stored in nested objects — see below). |
rcsb_find_go_terms | Resolve a free-text molecular function / biological process / cellular component to Gene Ontology ids (via EBI QuickGO), annotated with PDB entry counts — then search by rcsb_polymer_entity_annotation.annotation_lineage.id. |
rcsb_find_interpro_domains | Resolve a free-text protein domain / family / fold to InterPro and Pfam ids (via EBI Search), annotated with PDB entry counts — then search by rcsb_polymer_entity_annotation.annotation_id. |
rcsb_find_enzyme_classes | Resolve a free-text enzyme / reaction to Enzyme Commission (EC) numbers (via EBI Search/IntEnz), annotated with PDB entry counts — then search by rcsb_polymer_entity.rcsb_ec_lineage.id (hierarchical). |
rcsb_find_disease_terms | Resolve a free-text disease / condition to MONDO ids (via EBI OLS), annotated with PDB entry counts — then search by rcsb_uniprot_annotation.annotation_lineage.id (hierarchical, UniProt-based). |
rcsb_find_organisms | Resolve a free-text organism / common name / clade to NCBI Taxonomy ids (via UniProt taxonomy), annotated with PDB entry counts — then search by rcsb_entity_source_organism.taxonomy_lineage.id (hierarchical: a clade id matches every organism beneath it). |
Both attribute catalogs are generated from the live metadata schemas by scripts/generate_search_attributes.py. To search chemical-component attributes, find the path with rcsb_list_pdb_search_attributes(schema="chemical"), pass chemical_attributes=True to rcsb_query_attribute, and usually set return_type="mol_definition".
Nested attributes. An object can hold many annotations, many binding affinities, many citations. For attributes carrying a nested_group, the query shape selects the semantics: conditions built in one rcsb_query_attribute call, with nothing else in it, must hold on the same record; conditions in separate calls are matched independently against any record. Both are valid and mean different things — type=Kd with value<1 describes one measurement, while an InterPro id and a GO type are necessarily two different annotations.
Counting and faceting are output options on rcsb_search_request, not separate tools: every response includes total_count (the full match count — for "how many ..." run the search with limit=1 and read it), and passing facets returns a breakdown (terms/histogram/date_histogram/range/cardinality) instead of hits. A terms facet also tells you what your hits share, which is how a handful of results becomes a re-searchable value.
Grouping. group_by returns one representative per cluster — seqid_30 … seqid_95 for sequence-identity clusters, or uniprot to collapse by accession — with group_by_ranking choosing the representative. Requires return_type="polymer_entity"; the response reports group_count alongside total_count.
Sorting. sort_by (an attribute path) + sort_direction (asc/desc) replaces the default score ordering (for similarity searches this overrides the similarity-ranked order). Only attributes indexed for sorting work — those exposing exact_match (strings) or equals (numbers/dates) in rcsb_list_pdb_search_attributes; sorting is not available for return_type="mol_definition".
Paging. rcsb_search_request accepts limit (1–100, default 10) and offset (default 0), and each response reports total_count, has_more, and next_offset — call again with the same query document and offset=next_offset. For an explicit "ALL ..." request, all_hits=True returns the complete set in one call (refused above 10,000 hits, and it cannot be combined with offset).
There is one tool per Data API GraphQL root field. Each takes a list of IDs (singular lookups = a one-element list) plus an optional fields argument to override the curated default selection with your own GraphQL sub-selection. Unknown IDs are reported under not_found. Discover the paths to put in fields with rcsb_describe_data_object — browse a level, drill into a nested object with into=, or search the schema by keyword with query= + max_depth=. Every path it returns is verified against the live schema, so don't guess field names.
| Tool | Object | Example ID |
|---|---|---|
rcsb_get_entries | PDB entries | "4HHB" |
rcsb_get_polymer_entities | Polymer entities (protein/NA) | "4HHB_1" |
rcsb_get_nonpolymer_entities | Ligand/cofactor entities | "4HHB_3" |
rcsb_get_branched_entities | Carbohydrate entities | "5FMB_2" |
rcsb_get_polymer_entity_instances | Polymer chains | "4HHB.A" |
rcsb_get_nonpolymer_entity_instances | Bound-ligand instances | "4HHB.E" |
rcsb_get_branched_entity_instances | Glycan chains | "5FMB.C" |
rcsb_get_assemblies | Biological assemblies | "4HHB-1" |
rcsb_get_interfaces | Assembly interfaces | "1BMV-1.1" |
rcsb_get_chem_comps | Chemical components / ligands | "HEM", "ATP" |
rcsb_get_entry_groups | Entry groups | "G_1002266" |
rcsb_get_polymer_entity_groups | Polymer entity groups (seq. clusters) | "85_70" |
rcsb_get_nonpolymer_entity_groups | Non-polymer entity groups | "ATP" |
rcsb_get_uniprot | UniProt record (single) | "P69905" |
rcsb_get_pubmed | PubMed record (single, integer) | 6726807 |
rcsb_get_group_provenance | Grouping provenance (single) | "provenance_sequence_identity" |
rcsb_describe_data_object | Introspect an object's live GraphQL schema to build a fields= selection: browse a level, drill into a nested object with into=, or search by keyword with query= + max_depth= (flat, incl. nested + cross-object paths). Returns verified dotted paths. The Data API analogue of rcsb_list_pdb_search_attributes. | — |
The Search API only returns identifiers, so a search is the first step: batch the returned ids into the matching rcsb_get_* tool to fetch titles, organisms, and other metadata (these tools query the GraphQL endpoint, batching every requested ID into one request). All 16 typed tools are generated from a single registry in queries.py (DATA_OBJECTS), so adding a field or endpoint is a one-line change.
Maps alignments and positional annotations between sequence reference systems (UNIPROT, NCBI_PROTEIN, NCBI_GENOME, PDB_ENTITY, PDB_INSTANCE). Each tool takes an optional fields argument to override the default selection; use rcsb_describe_seqcoord_object to discover what fields are available.
This is the only RCSB API that cross-references NCBI (RefSeq protein / genome) — the Data API only knows UniProt. So "what NCBI proteins map to a PDB structure?" is answered by rcsb_seqcoord_alignments, not the Data API. PDB query ids must be entity-level (4HHB_1), not a bare entry (4HHB); for a whole entry, query each polymer entity.
| Tool | What it does |
|---|---|
rcsb_seqcoord_alignments | Cross-reference a sequence across PDB / UniProt / NCBI with aligned ranges (e.g. 4HHB_1 → NCBI proteins NP_000508, NP_000549). |
rcsb_seqcoord_annotations | Positional features of a PDB entity or instance (7CUT_1, 4HHB.A) from UniProt, the entity, its instances and their interfaces, optionally only some feature_types (ACTIVE_SITE); the sources follow from the types. |
rcsb_describe_seqcoord_object | Introspect the live schema to discover fields available on a seqcoord object (for use with fields=). |
| Tool | What it does |
|---|---|
rcsb_render_report | Render a structured report of search results — title, columns, rows and evidence — into a formatted HTML document for the user. |
RCSB hosts the server, so most clients need no install — point them at https://mcp-beta.rcsb.org/mcp (see Connect an agent). Install only to run it yourself, pin a version, or develop against it:
# run the published package without installing
uvx rcsb-mcp
pip install rcsb-mcp
rcsb-mcp is listed in the Official MCP Registry as io.github.rcsb/rcsb-mcp, so registry-aware clients can discover it directly.
For local development, install from the project root instead:
pip install -e .
uv pip install -e .
`
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