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MCP GeneLab Server

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Python
Hybrid

get_study_info

Read-onlyIdempotent

Retrieve detailed GeneLab study metadata, including assays with technology and measurement types, factors, and associated missions. Use for any study-metadata question.

Instructions

USE THIS TOOL (not the query tool) for any study-metadata question: "what assays does study X have", "tell me about OSD-267", project title, description, host organism, missions, factor space, or any inventory of a study's assays. Falling back to query for these reproduces the work this tool already does and loses the formatted markdown + inline CSV side-channel.

Return detailed information about a study, including its assays with their technology and measurement types.

This tool queries the GeneLab KG for:

  1. Study metadata (name, project title, description, organism, etc.)

  2. All assays for the study with their technology, measurement type, differential analysis method, factors, and materials

  3. Associated missions

For example, OSD-267 should return that it has both 16S and ITS amplicon sequencing data.

Input Schema

NameRequiredDescriptionDefault
study_idYesStudy identifier (e.g., 'OSD-267')
session_idNoSession id returned by `create_session()`. This server serves many users from one process; the session id is what keeps your output directory and generated plots private to you. Pass the SAME value on every tool call. If the server replies that the session is unknown or expired, call `create_session()` again and use the new id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world, so the safety profile is covered. The description adds genuine behavioral context beyond that: the structured return shape (metadata, assays with technology/measurement type/factors/materials, missions) and the 'formatted markdown + inline CSV side-channel' output behavior. It omits any caveats about missing studies or rate limits, keeping it short of a 5.

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?

Key routing advice is front-loaded and capitalized so it cannot be missed. There is mild redundancy, however: the opening routing block and the standalone sentence 'Return detailed information about a study, including its assays with their technology and measurement types' overlap with the numbered bullet list that follows.

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?

No output schema exists, so the description must explain return values, and it does so thoroughly via three enumerated return categories plus a worked example (OSD-267 -> 16S and ITS amplicon sequencing). Nothing needed to call the tool correctly is missing.

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?

Schema coverage is 100%: study_id and session_id are both fully documented in the schema, including the example 'OSD-267' and the session-privacy semantics. The description reinforces that the tool centers on a study but adds no new syntax or format detail. Baseline 3 applies when the schema carries the load.

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 (retrieve a study's metadata and assay inventory) and explicitly names the sibling it displaces ('not the `query` tool'). Concrete examples of questions it answers ('what assays does study X have', 'tell me about OSD-267') make the scope unmistakable.

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?

Gives explicit when-to-use guidance ('any study-metadata question'), enumerates the qualifying question types, and warns against the wrong path ('falling back to `query`... reproduces the work this tool already does'). This is the strongest possible routing guidance.

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

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