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Monday

by io.github.pipeworx-io

Monday Get Board

monday_get_board
Read-onlyIdempotent

Get board structure and metadata (e.g., board ID "12345"). Returns name, columns, groups, and item count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyYesMonday.com API token
board_idYesBoard ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoBoard ID
nameNoBoard name
stateNoBoard state
groupsNoBoard groups
columnsNoBoard columns
board_kindNoKind of board
updated_atNoLast update timestamp
items_countNoNumber of items in board

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "board_kind": {
+      "description": "Kind of board",
+      "type": "string"
+    },
+    "columns": {
+      "description": "Board columns",
+      "items": {
+        "properties": {
+          "id": {
+            "description": "Column ID",
+            "type": "string"
+          },
+          "title": {
+            "description": "Column title",
+            "type": "string"
+          },
+          "type": {
+            "description": "Column type",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "groups": {
+      "description": "Board groups",
+      "items": {
+        "properties": {
+          "color": {
+            "description": "Group color",
+            "type": "string"
+          },
+          "id": {
+            "description": "Group ID",
+            "type": "string"
+          },
+          "title": {
+            "description": "Group title",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "id": {
+      "description": "Board ID",
+      "type": "string"
+    },
+    "items_count": {
+      "description": "Number of items in board",
+      "type": "number"
+    },
+    "name": {
+      "description": "Board name",
+      "type": "string"
+    },
+    "state": {
+      "description": "Board state",
+      "type": "string"
+    },
+    "updated_at": {
+      "description": "Last update timestamp",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-monday-api-key",
+    "board_id": "12345"
+  }
+]
  3. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by specifying exactly what data is returned (name, columns, groups, item count), which is behavioral context beyond the annotations. There is no contradiction.

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 a single, front-loaded sentence that immediately states the tool's purpose and a key example. Every word contributes to understanding, with no fluff or repetition. It is appropriately concise for a simple two-parameter tool.

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 low complexity (2 required parameters, no nested objects), the description is complete. It covers the purpose, provides a concrete usage example, and mentions the nature of the return value, while the existing output schema handles detailed return structure. No critical information 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 description coverage is 100%: both _apiKey and board_id are documented in the input schema. The description adds a concrete example ('board ID 12345') but does not provide additional meaning beyond the schema. Baseline 3 is appropriate since the schema handles parameter documentation.

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 clearly states the action ('Get board structure and metadata'), identifies the resource (Monday board), and gives a concrete example (board ID '12345'). It also lists the return contents (name, columns, groups, item count), which distinguishes it from sibling tools like monday_list_boards (which lists boards) and monday_list_items (which lists items).

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

Usage Guidelines3/5

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

The description implies usage when you need board structure/metadata, but it provides no explicit guidance about when to use this tool versus alternatives. It does not mention exclusions, such as 'use monday_list_boards for board enumeration' or 'use monday_search_items for item-level queries'. The context of sibling tools is present but the description itself does not offer comparative guidance.

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

All Monday toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

The set has several overlapping tool clusters. ask_pipeworx and ask_pipeworx_beta are explicitly identical in behavior, ai_visibility_check and scan_competitor_ai_presence overlap heavily, and polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and polymarket_fill_risk all target opportunity-finding/fill-checking on prediction markets. While individual descriptions are detailed, an agent could easily pick the wrong tool among these near-duplicates.

Naming Consistency2/5

Naming is inconsistent across the surface. The monday_* and polymarket_* prefixes are consistent within their subgroups, and ask_pipeworx_* forms a family, but the rest mix verb_phrase (validate_claim, compare_entities, discover_tools), noun_phrase (entity_profile, recent_changes, suggest_questions), and bare verbs (remember, forget, recall) with no unifying pattern. This makes it hard to predict tool names.

Tool Count2/5

At 36 tools, the surface is overloaded. The Monday.com integration alone only needs 5 tools, and the remaining 31 are a sprawling research/meta-toolkit. Many of these could be consolidated (e.g., ask_pipeworx and ask_pipeworx_beta, or the several polymarket scanners), so the count feels inflated beyond what the server's core purpose requires.

Completeness3/5

The data-research and monitoring side is thorough, covering querying, grounding, comparison, profiling, entity resolution, subscriptions, memory, and feedback. However, the Monday.com integration is incomplete: it offers create/list/get/search for items but no update or delete operations, and no board creation or modification. This leaves the Monday workflow with dead ends.

Resources