monday_list_itemsList items in a board (e.g., board ID "12345"). Returns item ID, name, group, column values, and created date.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of items to return (default 20, max 50) | |
| _apiKey | Yes | Monday.com API token | |
| board_id | Yes | Board ID |
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Items in the board |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "items": {
+ "description": "Items in the board",
+ "items": {
+ "properties": {
+ "column_values": {
+ "description": "Column values for the item",
+ "items": {
+ "properties": {
+ "id": {
+ "description": "Column ID",
+ "type": "string"
+ },
+ "text": {
+ "description": "Column value text",
+ "type": "string"
+ },
+ "type": {
+ "description": "Column type",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "created_at": {
+ "description": "Item creation timestamp",
+ "type": "string"
+ },
+ "group": {
+ "description": "Item group",
+ "properties": {
+ "id": {
+ "description": "Group ID",
+ "type": "string"
+ },
+ "title": {
+ "description": "Group title",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "id": {
+ "description": "Item ID",
+ "type": "string"
+ },
+ "name": {
+ "description": "Item name",
+ "type": "string"
+ },
+ "updated_at": {
+ "description": "Last update timestamp",
+ "type": "string"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "items"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "_apiKey": "your-monday-api-key",
+ "board_id": "12345"
+ },
+ {
+ "_apiKey": "your-monday-api-key",
+ "board_id": "12345",
+ "limit": 30
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds useful behavioral context by specifying the return fields (item ID, name, group, column values, created date), which goes beyond the annotations and helps set expectations. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately states the action, gives an example, and lists return fields. Every word earns its place; no waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with an output schema and rich annotations, the description is sufficient. It covers the core functionality and return values, though it omits details like pagination or default limit, which are documented in the schema. The presence of an output schema reduces the need to explain return values further.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds a minor example (board ID '12345') and hints at the board_id parameter but does not explain limit or _apiKey beyond what the schema provides. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair ('List items in a board') and includes a concrete example (board ID '12345'), making its purpose unmistakable. It also clearly distinguishes from sibling tools like monday_list_boards (which lists boards) and monday_search_items (which searches).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need items from a specific board) but does not explicitly state when to use this tool versus alternatives like monday_search_items or monday_get_board. No exclusions or alternative guidance is provided, though the board-focused wording provides some implied context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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.