Skip to main content
Glama
informatics-isi-edu

Deriva MCP Server

Official

add_dataset_members

Add records from registered tables to a dataset as members, auto-incrementing its minor version. Supports RID lists or grouped by table for faster bulk additions.

Instructions

Add records as dataset elements. Auto-increments minor version.

Records must be from tables registered as dataset element types. Use add_dataset_element_type() to register a table, or list_dataset_element_types() to see which tables are already registered.

Accepts members in two forms:

List of RIDs (member_rids): Each RID is auto-resolved to its table. Simpler but slower for large numbers.

Dict by table name (members_by_table): Maps table names to RID lists. Faster (skips RID resolution) and lets you add members of different types in one call. Recommended when you know the table names.

Exactly one of member_rids or members_by_table must be provided.

Args: dataset_rid: The RID of the dataset to add members to. member_rids: List of RIDs to add (e.g., ["2-ABC", "2-DEF"]). Auto-resolves each RID to its table. members_by_table: Dict mapping table names to RID lists (e.g., {"Subject": ["2-ABC"], "Observation": ["2-DEF", "2-GHI"]}). Faster than member_rids for large datasets. description: Optional description for the version increment that records why these members were added. Stored in the dataset history.

Returns: JSON with status, added_count, dataset_rid.

Example: add_dataset_members("1-ABC", member_rids=["2-DEF", "2-GHI"]) add_dataset_members("1-ABC", members_by_table={"Subject": ["2-DEF"], "Image": ["2-GHI"]})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_ridYes
descriptionNo
member_ridsNo
members_by_tableNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description discloses key side effects: auto-increments minor version, version description stored in history, and requires registered tables. It also clarifies the mutual exclusivity of member_rids and members_by_table, which is a behavioral constraint not visible in the schema.

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

Conciseness5/5

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

The description is well-structured with sections (Args, Returns, Example) and every sentence provides actionable information. The examples at the end effectively illustrate usage without redundancy.

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?

Despite no annotations, the description covers prerequisites, two input forms, mutual exclusivity, return values, and side effects. The presence of an output schema doesn't hurt; the description still provides enough context for correct invocation.

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

Parameters5/5

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

Schema coverage is 0%, but the description fully explains each parameter with concrete examples (e.g., '{"Subject": ["2-ABC"]}') and clarifies the trade-off between member_rids and members_by_table. This significantly adds meaning beyond the bare schema.

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?

The first sentence 'Add records as dataset elements' uses a specific verb and resource, and 'Auto-increments minor version' adds a distinct behavioral trait. This clearly distinguishes it from siblings like delete_dataset_members or add_dataset_child.

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?

The description states a prerequisite (records must be from registered tables) and explicitly names alternative tools (add_dataset_element_type, list_dataset_element_types). It also explains when to use each input form, recommending members_by_table when table names are known, and enforces exactly one of the two parameters.

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/informatics-isi-edu/deriva-mcp'

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