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RNAcentral MCP Server

RNAcentral MCP Server

Official
by RNAcentral

search_sequence

Launch a background RNA sequence search across selected or all RNAcentral databases, returning a job ID to poll for results.

Instructions

Start a background search of the RNAcentral database for a given RNA sequence. Returns a job ID immediately; the search can take minutes to hours under load. Poll get_sequence_search_results with the job ID until it reports results.

Args: sequence: The RNA sequence to search for databases: Optional list of specific databases to search within (default: all databases)

Returns: A job ID to pass to get_sequence_search_results

Input Schema

NameRequiredDescriptionDefault
sequenceYes
databasesNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that the operation is asynchronous, returns immediately with a job ID, and can take minutes to hours under load. It omits permission/auth requirements and any rate-limit or failure-mode detail, but the latency and non-blocking behavior are exactly the traits an agent most needs.

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?

Front-loaded with the action and the async contract, then structured Args/Returns sections. There is minor redundancy: "Returns a job ID immediately" is restated in the Returns block, and the output schema already declares the return shape.

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?

For a two-parameter async search tool with no annotations, the description supplies the full call-and-poll workflow, the latency expectation, and both parameter meanings. Nothing an agent needs in order to invoke it correctly and follow up is missing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate, and it does: both parameters are explained, including that databases is optional, is a list of specific databases, and defaults to all databases. It does not give valid database name examples or sequence format constraints, which is the remaining gap.

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?

States a specific verb and resource ("Start a background search of the RNAcentral database for a given RNA sequence") and immediately makes the async job model explicit, which distinguishes it from the sibling get_sequence_search_results that only retrieves results. An agent can tell the two apart without opening either schema.

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

Usage Guidelines4/5

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

Gives clear operational guidance: call this to start, then poll get_sequence_search_results with the returned job ID until results appear. It does not address when to prefer the sibling query_rnacentral instead, nor any exclusion for short/ambiguous sequences, so it falls short of full when/when-not coverage.

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