Skip to main content
Glama

noticed

by so.noticed.mcp
OverviewDiscussionsAdmin

create_list

Create a list — a described set of people (e.g. 'Seed investors', 'Design candidates'). The description is REQUIRED and is the goal noticed matches people against, so write it specifically ('pre-seed investors who back dev tools in Europe'): AI suggestions are off by default. Set ai_enabled=true to have noticed propose people from the network to add, which the user confirms or rejects. The title is auto-generated from the description unless you pass a name. Returns the new list_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoShort title for the list; auto-generated from the description when omitted.
ai_enabledNoWhether noticed suggests people for this list (default false).
descriptionYesWhat the list is FOR, in the user's words — the goal noticed matches people against. REQUIRED. Be specific; a vague description means vague suggestions.
organization_idNoCreates a TEAM list owned by that organization (from account_status.teams). Omit for a personal list.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesWhether noticed completed the operation.
dataNoThe operation result when ok is true.
errorNoA human-readable error when ok is false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedOutput schema / properties / data / properties / canonical_url
      Added value: +{
+  "format": "uri",
+  "type": "string"
+}
    • addedOutput schema / properties / data / properties / review_url
      Added value: +{
+  "format": "uri",
+  "type": "string"
+}
    • changedOutput schema / properties / data / required
      Previous value: -[
-  "list_id",
-  "name"
-]New value: +[
+  "list_id",
+  "name",
+  "canonical_url",
+  "review_url"
+]
  2. Changed1 schema field changed
    • changedInput schema / properties / ai_enabled / description
      Previous value: -"Whether noticed suggests people for this list (default true)."New value: +"Whether noticed suggests people for this list (default false)."
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "data": {
+      "additionalProperties": true,
+      "description": "The operation result when ok is true.",
+      "properties": {
+        "ai_enabled": {
+          "type": "boolean"
+        },
+        "description": {
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "list_id": {
+          "type": "string"
+        },
+        "member_count": {
+          "type": "number"
+        },
+        "name": {
+          "type": "string"
+        },
+        "organization_id": {
+          "$ref": "#/properties/data/properties/description"
+        },
+        "pending_count": {
+          "type": "number"
+        }
+      },
+      "required": [
+        "list_id",
+        "name"
+      ],
+      "type": "object"
+    },
+    "error": {
+      "description": "A human-readable error when ok is false.",
+      "type": "string"
+    },
+    "ok": {
+      "description": "Whether noticed completed the operation.",
+      "type": "boolean"
+    }
+  },
+  "required": [
+    "ok"
+  ],
+  "type": "object"
+}
  4. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations provide no hints (all false), so the description carries the full burden. It reveals that the description is the matching goal, that AI suggestions are off by default and can be enabled, that the user confirms/rejects suggestions, that the title auto-generates, and that it returns a list_id. This is rich behavioral context beyond what annotations or schema convey, and nothing contradicts the annotations.

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?

The description is a single paragraph but efficiently packs all essential information: purpose, required parameter, example specificity, default behavior, optional flags, and return value. It is slightly long but each sentence earns its place. The purpose is front-loaded, and there is no redundant or filler content.

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?

Given the tool's complexity (create operation with a required semantic parameter and optional configuration) and the availability of an output schema (implied by 'Returns the new list_id'), the description covers everything an agent needs: the required parameter, optional parameters and their effects, default behavior, and the return value. It leaves no critical gap for correct invocation.

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 coverage is 100% with each parameter having a description, so the baseline is 3. The tool description adds value by explaining the description parameter's role as the matching goal and giving concrete examples, clarifying ai_enabled behavior, and noting that name is auto-generated. This goes beyond the schema, though the schema already covers each parameter adequately.

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 description states a specific verb (create) and resource (list, a set of people), and distinguishes it from siblings like add_to_list, update_list, and delete_list by focusing on the creation aspect. It also clarifies the core semantic of a list as a described set of people, which is not obvious from the name alone.

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?

The description explains the required description parameter and how to write it effectively, and covers when to enable ai_enabled. It implicitly distinguishes creation from updating (update_list) and adding (add_to_list) through its purpose, though it does not explicitly state 'use this when creating a new list; use update_list to modify existing.' The guidance is clear but lacks explicit exclusions or alternative routing.

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

All noticed toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources