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An MCP server that provides tools for searching and fetching protein data from the UniProt database using the unipressed library.
An MCP server that provides tools for searching and fetching protein data from the UniProt database using the unipressed library.
An MCP (Model Context Protocol) server that provides tools for querying the UniProt protein database using the unipressed Python library.
uv sync
This will create a virtual environment and install all dependencies.
uv sync --extra dev
This installs the package with development dependencies (pytest, etc.).
uvx uniprot-unipressed-mcp
Or from a git repository:
uvx --from git+https://github.com/pansapiens/uniprot-unipressed-mcp uniprot-mcp
fastmcp run src/uniprot_mcp/server.py:mcp --transport http --port 8007
Add the server using the Claude Code CLI:
claude mcp add uniprot-unipressed-mcp -- uvx git+https://github.com/pansapiens/uniprot-unipressed-mcp
Or manually add to your MCP configuration (Claude Code, Cursor, etc.):
{
"mcpServers": {
"uniprot-unipressed-mcp": {
"command": "uvx",
"args": ["git+https://github.com/pansapiens/uniprot-unipressed-mcp"]
}
}
}
Tool responses are returned in JSON format by default. To receive TOON format responses instead, use the response_format parameter with value "toon":
# JSON format (default)
result = uniprot_search(query="gene:BRCA1")
# TOON format
result = uniprot_search(query="gene:BRCA1", response_format="toon")
Search the UniProt protein database using query syntax.
Parameters:
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| query | string | Yes | - | UniProt query string |
| database | string | No | "uniprotkb" | Database to search: uniprotkb, uniparc, uniref |
| limit | integer | No | 10 | Results per page (1-100) |
| fields | list[string] | No | None | Return fields to include |
| cursor | string | No | None | Pagination cursor from previous result |
| response_format | string | No | "json" | Response format: "json" (default) or "toon" |
Example queries:
gene:BRCA1 # Search by gene name
organism_id:9606 # Human proteins (NCBI taxonomy ID)
(gene:BRCA*) AND (organism_id:10090) # Mouse BRCA genes with wildcard
length:[500 TO 700] # Proteins of specific length range
keyword:kinase # By UniProt keyword
family:serpin # By protein family
ec:3.2.1.23 # By enzyme classification
reviewed:true # Only Swiss-Prot reviewed entries
Response:
By default, responses are returned in JSON format. When response_format="toon" is specified, responses are returned in TOON format (a compact string):
JSON format (default):
{
"results": [...],
"total": 1234,
"nextCursor": "eyJvZmZzZXQiOiAxMH0="
}
TOON format:
results[10]:
- entryType: UniProtKB reviewed (Swiss-Prot)
primaryAccession: P38398
secondaryAccessions[7]: E9PFZ0,O15129,Q1RMC1,Q3LRJ0,Q3LRJ6,Q6IN79,Q7KYU9
uniProtkbId: BRCA1_HUMAN
...etc...
Fetch specific protein entries by their UniProt accession IDs.
Parameters:
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| ids | list[string] | Yes | - | UniProt accession IDs to fetch |
| database | string | No | "uniprotkb" | Database to fetch from |
| fields | list[string] | No | None | Return fields to include |
| response_format | string | No | "json" | Response format: "json" (default) or "toon" |
Example:
uniprot_fetch(ids=["P62988", "A0A0C5B5G6"])
Response:
By default, responses are returned in JSON format. When response_format="toon" is specified, responses are returned in TOON format (a compact string):
JSON format (default):
{
"results": [...],
"found": 2,
"requested": 2
}
TOON format:
results[10]:
- entryType: UniProtKB reviewed (Swiss-Prot)
primaryAccession: P38398
secondaryAccessions[7]: E9PFZ0,O15129,Q1RMC1,Q3LRJ0,Q3LRJ6,Q6IN79,Q7KYU9
uniProtkbId: BRCA1_HUMAN
...etc...
The server uses cursor-based pagination for search results. When more results are available, the response includes a nextCursor field. Pass this cursor in subsequent requests to retrieve the next page:
# First request
result1 = uniprot_search(query="organism_id:9606", limit=10)
# Get next page using cursor
if "nextCursor" in result1:
result2 = uniprot_search(
query="organism_id:9606",
limit=10,
cursor=result1["nextCursor"]
)
| Database | Description |
|---|---|
| uniprotkb | UniProt Knowledgebase - curated protein sequences and annotations |
| uniparc | UniProt Archive - comprehensive protein sequence archive |
| uniref | UniProt Reference Clusters - clustered protein sequences |
Common return fields include:
accession - UniProt accession numberid - Entry namegene_names - Gene namesprotein_name - Protein namesorganism_name - Source organismorganism_id - NCBI taxonomy IDlength - Sequence lengthmass - Molecular masssequence - Amino acid sequencecc_function - Function annotationcc_subcellular_location - Subcellular locationSee the UniProt return fields documentation for the complete list.
{
"mcpServers": {
"uniprot-unipressed-mcp": {
"command": "uv",
"args": ["--directory", "/path/to/uniprot-unipressed-mcp", "run", "-m", "uniprot_mcp.server"]
}
}
}
npx @modelcontextprotocol/inspector uv --directory $(pwd) run -m uniprot_mcp.server
uv run pytest
This runs all unit tests. Integration tests (which require network access to the UniProt API) are skipped by default.
Integration tests can be enabled using an environment variable:
RUN_INTEGRATION_TESTS=1 uv run pytest
Or run only integration tests:
RUN_INTEGRATION_TESTS=1 uv run pytest -m integration
uv run pytest --cov=uniprot_mcp
To include integration tests in coverage:
RUN_INTEGRATION_TESTS=1 uv run pytest --cov=uniprot_mcp
MIT
Выполни в терминале:
claude mcp add uniprot-unipressed-mcp -- npx Безопасность
Низкий рискАвтоматическая эвристика по публичным данным — не гарантия безопасности.