Lichess MCP

get_leaderboard

Retrieve ranked player lists for specific chess time controls or variants on Lichess, showing top performers in categories like bullet, blitz, classical, and chess960.

Instructions

Get the leaderboard for a single speed or variant

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": {
      "perfType": "<perfType>"
    },
    "name": "get_leaderboard"
  }
}

Input Schema

Name	Required	Description	Default
`nb`	No	How many users to fetch (1-200)
`perfType`	Yes	The speed or variant

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 18, 2025

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool's function but omits critical details like whether it requires authentication, has rate limits, returns paginated results, or includes error handling. For a read operation with no annotation support, this is insufficient.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.

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

Completeness2/5

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

For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain the return format (e.g., JSON structure, fields like rankings or scores), error conditions, or authentication requirements, leaving significant gaps for an AI agent to use it effectively.

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?

The input schema has 100% description coverage, clearly documenting both parameters ('nb' for count and 'perfType' for speed/variant). The description adds no additional semantic context beyond what the schema provides, such as explaining the leaderboard format or default behaviors, so it 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.

Purpose4/5

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

The description clearly states the action ('Get') and resource ('leaderboard'), specifying it's for a single speed or variant. It doesn't explicitly differentiate from sibling tools like 'get_all_top_10' or 'get_user_performance', but the focus on leaderboard retrieval is unambiguous.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'get_all_top_10' or 'get_user_profile' for leaderboard-related data. The description lacks context on prerequisites, such as authentication or rate limits, leaving usage unclear.

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

Deploy Server