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Little Green Light MCP Server

Little Green Light MCP Server

by WillHeadlee
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

create_group_with_members

Create a static group and add members in a single call. Handles partial failures without failing the whole operation.

Instructions

Creates a new LGL group and adds one or more constituents to it in a single call. This is the closest API-native substitute for LGL's UI-only saved/dynamic Lists — LGL's API has no endpoint to create or edit a List at all. Unlike a List, a group is a static set of members (not a live, re-run query); add or remove members afterward with add_constituent_to_group / remove_constituent_from_group. Partial failures (e.g. one bad constituent_id) don't fail the whole call — check each entry's result.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "group_name": "<group_name>",
      "constituent_ids": "<constituent_ids>"
    },
    "name": "create_group_with_members"
  }
}

Input Schema

NameRequiredDescriptionDefault
group_nameYesName for the new group, e.g. "Major Donors Q3 2026"
constituent_idsYesConstituent IDs to add as members of the new group

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.7.0

TDQS

A4.6/5.0
Behavior5/5

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

Discloses partial failure behavior (bad constituent_id doesn't fail entire call). Annotations (readOnlyHint=false, destructiveHint=false) consistent; no contradictions.

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?

Three sentences, each valuable: main action, comparison to Lists, partial failure handling. Front-loaded and no wasted words.

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

Completeness4/5

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

Covers purpose, usage, and partial failures. Lacks explicit return value description, but as a creation tool it's adequate for agent use.

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% with descriptions. Description adds no new information beyond schema for the two parameters. Baseline score of 3 is appropriate.

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?

Clearly states it creates a new LGL group and adds constituents in one call. Distinguishes from related tools like add_constituent_to_group and notes it's a substitute for Lists.

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 says when to use (creating a group with members in one call) and when not (for dynamic Lists, as API lacks List endpoints). Provides alternatives for later modifications.

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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