UniProt & Proteins API MCP Server

The UniProt MCP Server bridges the gap between AI assistants and one of biology’s most authoritative protein databases. By exposing UniProt data through the Model Context Protocol, it allows Claude or other MCP‑compatible assistants to retrieve protein names, functions, sequences, lengths and organism information with a single API call. This eliminates the need for developers to embed complex HTTP logic or maintain their own database copies, streamlining bioinformatics workflows and enabling rapid prototyping of science‑driven conversational agents.

At its core, the server offers two principal tools: for single accession queries and for bulk lookups. Both tools accept standard UniProt accession numbers, returning structured JSON that includes the protein’s full amino‑acid sequence and functional annotations. A 24‑hour cache, implemented with an ordered dictionary, ensures that repeated requests for the same proteins are served instantly while keeping data fresh. The server also handles rate limiting, retries, and detailed error reporting—providing clear feedback for invalid accessions (404), network failures, or API throttling (429).

For developers building AI‑powered biology assistants, this server unlocks several practical use cases. A medical chatbot can answer “What is the function of protein P98160?” in real time, while a research assistant can compare multiple proteins by asking for both P04637 and P02747. Because the data is fetched on demand, developers avoid storing large FASTA files locally and can focus on higher‑level logic such as hypothesis generation or data visualization. The MCP integration means the server can be added to a Claude Desktop configuration with a single JSON entry, making it trivial to switch between local and remote data sources.

Unique advantages include the seamless batch retrieval capability, which is not commonly found in other MCP servers. By allowing an array of accessions to be queried in one call, the server reduces network overhead and latency—a critical factor when an assistant needs to present comparative analyses quickly. Additionally, the explicit error handling and logging give developers confidence that their applications can gracefully recover from common API pitfalls.

In summary, the UniProt MCP Server is a lightweight, highly reliable bridge that empowers AI assistants to deliver accurate protein information on demand. Its simple tool interface, caching strategy, and robust error management make it an indispensable component for any bioinformatics or life‑science application that relies on up‑to‑date protein data.