Liquipedia MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct entity or operation (wikitext, matches, placements, players, standings, teams, tournaments, generic query), with clear descriptions that differentiate them. No obvious overlap.
Naming Consistency3/5
Most tools use 'list_' prefix for fetching lists, but 'get_wikitext' uses 'get_' and 'query' is a bare verb. This inconsistency in naming convention could cause confusion about the action being performed.
Tool Count4/5
8 tools is a reasonable number for an esports wiki server, covering major entities. Not too few or too many, but a few more specialized tools could be added without bloat.
Completeness5/5
The tool set covers the main entities (matches, players, teams, tournaments, standings, placements) plus raw wikitext retrieval and a generic query tool for any other datapoint, ensuring no obvious gaps.
Average 3.6/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It reveals return fields (tournament name, dates, prize pool, etc.) which is helpful but does not disclose any behavioral traits like pagination, error handling, or rate limits. The description adds some value beyond the schema but could be more transparent.
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 extremely concise, consisting of two sentences that directly state the action and the return fields. There is no redundancy or wasted words, making it easy for an AI agent to parse quickly.
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?
Given 8 parameters and no output schema, the description covers the core purpose and return fields but omits the required 'wiki' parameter and does not explain how filters combine. It is adequate for a basic understanding but leaves gaps for complete usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description only restates a subset of filters (name, date, organizer) and does not enhance understanding of complex parameters like 'conditions' or 'query'. It provides minimal additional semantic value beyond what is already in the schema.
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 that the tool fetches tournaments for a wiki with filtering by name, date, or organizer. However, it does not differentiate from sibling tools like list_matches or list_teams, which might lead to confusion about when to use this tool.
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?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. It only describes the tool's basic functionality without context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. 'Fetch' implies read-only but is not explicitly stated. No mention of side effects, rate limits, or authorization needs. Minimal transparency.
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?
Single sentence of 17 words, front-loaded with verb and resource. No wasted words; every word adds value.
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?
Given 7 parameters and no output schema, the description is too brief. It does not hint at how to use commonly needed filters like opponentname, tournament, or conditions, leaving the agent to infer solely from schema.
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% (all parameters described in schema), so baseline is 3. The description adds no extra parameter-level detail beyond what schema already provides.
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 it fetches tournament placements/results for a team or player on a wiki, and specifies returned fields (placement, prize money, tournament). This distinguishes from siblings like list_matches, though it could more explicitly differentiate from list_standings.
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 explicit guidance on when to use this tool vs alternatives. The description implies use for team/player-specific placements but does not list exclusions or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It fails to mention that this is a read-only operation, potential rate limits, or any side effects. It only describes the basic functionality.
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 concise sentence that covers the purpose and key features. It is front-loaded and easy to parse, though it could be slightly restructured for clarity on output fields.
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?
Given 8 parameters, no output schema, and no annotations, the description provides adequate but not comprehensive context. It mentions return fields but omits default behavior (e.g., limit default is 20) and pagination details.
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%, so the baseline is 3. The description adds minimal value beyond schema by summarizing filter options, but it does not enrich individual parameter meanings beyond what the schema already provides.
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 ('Fetch players'), the resource ('for a wiki'), filtering options, and return fields. It effectively distinguishes from sibling tools like list_teams or list_matches.
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 context ('Fetch players for a wiki') and mentions filters but does not explicitly provide when-to-use or when-not-to-use guidance compared to siblings. No alternative tools are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It mentions returning upcoming and completed matches with specific fields, but does not disclose rate limits, auth needs, error conditions, or pagination behavior. It is adequate but not comprehensive.
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 two sentences, front-loaded with purpose and filters, and includes return value hints. No unnecessary words; every sentence adds value.
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?
Given 8 parameters and no output schema, the description covers high-level purpose and return fields, but lacks details on how filters combine, default limits, or the 'conditions' parameter. It is adequate but could be more complete.
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 schema description coverage is 100%, so baseline is 3. The description adds minor context about which filters are available (team/opponent, tournament, date) and what is returned, but does not significantly enhance parameter understanding beyond the schema.
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 tool fetches matches with filters, using specific verb 'Fetch' and resource 'matches'. However, it does not differentiate from sibling tools like 'query' or 'list_standings', missing some sibling distinction.
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?
It lists filters but lacks explicit guidance on when to use this tool versus alternatives. No 'when to use' or 'when not to use' is provided; usage is implied through the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It describes fetching and returning metadata, which is a read operation, but does not disclose behavioral traits such as pagination behavior, rate limits, or authentication needs. The limit parameter in schema indicates default/max but is not mentioned in description.
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 sentence followed by a bullet list of return fields. It is concise and front-loaded, with no redundant or extraneous information.
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?
Given the tool has 8 parameters and no output schema or annotations, the description is somewhat incomplete. It does not mention that the 'wiki' parameter is required, nor does it explain the 'conditions' parameter or the interaction between structured filters and raw conditions. The returned field list is helpful but lacks detail on the return structure.
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 baseline is 3. The description highlights three filter parameters (name, region, location) but does not add meaning to other parameters (limit, order, query, conditions, wiki) beyond what the schema provides. It repeats some schema info but does not enhance understanding.
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 ('Fetch teams') and the resource ('teams for a wiki'), with explicit filter options and return fields. It effectively distinguishes from sibling tools like list_players or list_matches by focusing on team metadata.
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?
No explicit guidance on when to use this tool versus alternatives. The description implies usage for team data retrieval, but does not exclude cases where other list tools might be more appropriate (e.g., use list_players for player data).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It discloses 'no API key required' and the return format, but lacks details on limits, errors, or performance.
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?
Two sentences with no waste. Front-loaded with action and resource, efficient use of space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description covers purpose, use cases, return format, and authentication. Could add page limits or failure modes, but sufficient for a simple fetch tool.
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?
All parameters are documented in the input schema (100% coverage). The description adds no new parameter-level semantics beyond what the schema provides, meeting baseline.
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 'Fetch the raw wikitext' with a specific resource (Liquipedia pages via MediaWiki API). It distinguishes from sibling structured-data tools by noting it's for content 'not exposed as structured datapoints'.
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?
Explicitly says 'Useful for infoboxes, rosters, and page content not exposed as structured datapoints', which guides selection. Does not explicitly state when not to use, but the contrast with structured siblings is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that results are 'SORTED by placement' and use the 'latest round snapshot', but lacks detail on caching, rate limits, or error behavior. The disclosed traits are adequate but not comprehensive.
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 extremely concise—two sentences that front-load the purpose and provide essential usage guidance. Every sentence is meaningful and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the output (teams sorted by placement, points, latest round snapshot) despite the absence of an output schema. It covers key behavioral aspects for a filtered-list tool. Missing details like pagination or error cases but still fairly complete given the tool's simplicity.
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%, so the baseline is 3. The description adds minimal extra meaning beyond the schema, only providing a usage example for the 'tournament' parameter. It does not clarify parameter formats or constraints beyond what the schema already states.
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 uses a specific verb ('Fetch') and resource ('ranked standings / points table'), clearly distinguishing it from siblings like list_matches or list_placements by referencing battle-royale events and group-stage tables.
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 provides strong context for when to use ('Ideal for battle-royale events... and any group-stage points table') and includes a concrete example for the tournament parameter. However, it does not explicitly state when not to use this tool or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the use of Liquipedia's condition syntax and that conditions are combined with structured filters (though no structured filters parameter exists, which may cause confusion). It does not mention return format, pagination behavior beyond offset/limit, rate limits, or authentication. This is adequate for a read-only query but leaves gaps in behavior understanding.
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 two sentences, front-loaded with the core purpose ('low-level access'). The second sentence provides essential usage details without fluff. Every part is substantive, and there is no redundancy with the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 8 parameters, no output schema, and no annotations. The description covers the main functionality and condition syntax, but it lacks details about the return format (e.g., structure of the output) and how multiple wikis are combined. Given the absence of output schema, a brief mention of what the response contains would improve completeness. Still, the core purpose is well-covered.
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%, so baseline is 3. The description adds value by explaining the raw conditions syntax with an example and mentioning that conditions are combined with structured filters. However, it does not provide additional semantics for other parameters (e.g., how 'query' differs from 'conditions') beyond the schema. The marginal improvement over schema justifies a score of 3.
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 it provides 'low-level access to any Liquipedia v3 datapoint' and lists all supported datapoints. The verb 'query' combined with the explanation of the condition syntax makes the purpose unmistakable. It also implicitly distinguishes from sibling list tools (e.g., list_matches) by positioning itself as lower-level.
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 that users need to provide a wiki and optional raw conditions, and it hints at usage by mentioning the condition syntax. However, it does not explicitly state when to choose this tool over siblings (e.g., when custom queries are needed vs. when to use for simple listing), and it lacks a 'when not to use' note. Still, the guidance is clear enough for most agents.
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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