Crawlora MCP

chesscom_match_live_board

Read-only

Get one board from a public live team match. The service calls Chess.com’s documented Published-Data API serially. This independent service is not affiliated with Chess.com; do not use results for AI training or dataset creation.

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": {
      "id": "<id>",
      "board": "<board>"
    },
    "name": "chesscom_match_live_board"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	Required source id.
`board`	Yes	Required source board.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 13, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, and the description adds genuinely useful context beyond them: upstream calls are made serially (implying latency/throughput limits), the data source is Chess.com's Published-Data API, and the service is unaffiliated. It still says nothing about failure modes, rate limits, or what a missing board returns, and the return shape is covered by the output schema.

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?

Purpose is front-loaded in the first sentence, and the following sentences add provenance and a usage restriction that matters to an AI caller. The affiliation disclaimer is slightly verbose but not filler that obscures the tool's function.

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

Completeness3/5

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

With an output schema and annotations present, the definition need not explain return values, and the serial-call note covers behavior. The remaining gap is that neither description nor schema clarifies the identifier domain for id/board, which is the main thing an agent could get wrong on a two-required-parameter call.

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%, so both parameters are documented in the schema, but only thinly ("Required source id", "Required source board"). The description adds no meaning about what the id refers to (match id, slug, URL) or what board accepts, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Get one board from a public live team match" gives a specific verb (get), resource (board) and scope (public, live, team match). The live/board qualifiers make it distinguishable from whole-match and archive siblings even though no sibling is named.

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 "live" and "one board" scoping implies when this tool applies, but there is no explicit when-to-use versus when-not, and no pointer to alternatives such as the non-live match board or the full live match tool. The agent must infer selection from the name and scope words.

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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