Context7
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作者による説明(英語の原文)
MCP server to search, inspect, and cross-reference RCSB Protein Data Bank structures
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"rcsb": {
"command": "uvx",
"args": [
"rcsb-mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add rcsb -- uvx rcsb-mcpプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"rcsb": {
"command": "uvx",
"args": [
"rcsb-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"rcsb": {
"type": "stdio",
"command": "uvx",
"args": [
"rcsb-mcp"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント rcsb で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.23.0)がレジストリに届いたのは14 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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 .
`
冒頭だけを表示しています。続きはリポジトリで読めます