Skip to main content
Glama

uniprot_target_dossier

Read-only

Aggregates UniProt entry data into a structured dossier for drug-discovery workflows, covering identity, function, structure, drug targets, and disease associations to guide subsequent deep dives.

Instructions

One-call comprehensive characterisation of a UniProt entry, structured for drug-discovery / clinical workflows. Composes nine views over the same entry plus one FASTA fetch (so two upstream network calls, not nine):

Identity · Function · Sequence chemistry · Structural evidence (PDB count + best-resolution + AlphaFold model id + InterPro count) · Drug-target context (ChEMBL ids, DrugBank count) · Disease associations (with MIM IDs) · Variants count · Functional annotations (top GO MF, subcellular, ECO diversity) · Cross-references summary

For per-residue pLDDT confidence call uniprot_get_alphafold_confidence separately. For full disease detail call uniprot_get_disease_associations. The dossier is the entry- level summary that decides which deeper tools are worth calling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accessionYesUniProt accession, e.g. 'P04637' (human TP53) or 'P38398' (human BRCA1). Both reviewed (Swiss-Prot) and unreviewed (TrEMBL) accessions are accepted; case-sensitive.
response_formatNo'markdown' (default) for a human-readable report with a provenance footer, or 'json' for a machine-parseable structured payload with the same data. Any other value is rejected.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses network call optimization ('two upstream network calls, not nine') and output format options, adding value beyond readOnlyHint and openWorldHint annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with bullet points, front-loaded purpose. Slightly lengthy but every sentence earns its place; compresses 9 views into clear enumeration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Fully explains purpose, usage context, behavioral details, and parameter constraints. Output schema handles return specifics; description complete for entry-level summary tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters well-documented in schema (100% coverage). Description adds minor detail ('Any other value is rejected' for response_format) but largely redundant.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'One-call comprehensive characterisation of a UniProt entry' and lists nine specific views, distinguishing it from sibling tools that provide narrower or deeper detail.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly directs to use for entry-level summary to decide on deeper tools, and provides alternative tools for specific needs (e.g., pLDDT, full disease detail).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/smaniches/uniprot-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server