liquipedia-dota2-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct purpose: search for entities, then retrieve specific details for tournaments, teams, players, or matches. There is no overlap, and the descriptions clearly differentiate when to use each one.
Naming Consistency5/5All tools follow a consistent verb_noun pattern in snake_case (e.g., search_dota2_entities, get_dota2_tournament, list_dota2_matches). The naming is predictable and easy to understand.
Tool Count5/5With 5 tools, the server is well-scoped for a focused domain (Dota 2 esports data). It provides essential operations without unnecessary bloat or missing core functionality.
Completeness5/5The toolset covers the full lifecycle of querying Dota 2 entities: search to find canonical titles, then retrieve details for tournaments, teams, players, and matches. There are no obvious gaps for a read-only information retrieval server.
Average 4.3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already provide readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral context by labeling the tool as 'expensive', which guides the agent on cost implications beyond what annotations capture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste. The first sentence states the purpose and scope, the second adds usage guidance and cost context. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists (reducing need to describe return values), the description still lacks coverage of the optional filtering parameters (to, from, limit, status). For a tool with 6 parameters and 2 required, the minimal description leaves gaps in how to construct correct invocations, especially for date ranges and result limits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 17% schema description coverage (only canonical_title has a description), the description should compensate but does not. It mentions 'for one exact tournament or team page' which hints at scope_type and canonical_title, but completely omits explanations for the other four parameters (to, from, limit, status). The agent must infer their meaning from names alone, which is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists schedule or result rows for one exact tournament or team page. This is a specific verb-resource combo that distinguishes it from sibling tools like search_dota2_entities (which searches broadly) or get_dota2_tournament (which fetches tournament details).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'use only when the user asks about matches, schedules, scores, or results' and notes it's an 'expensive match-specific lookup'. This provides clear context for when to invoke, though it does not explicitly list exclusions or name alternatives beyond the implied contrast with siblings.
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?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety and idempotency. The description adds the source constraint (canonical title from search) but no further behavioral traits (e.g., auth, rate limits). No contradiction 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence front-loads the purpose and source. Every word contributes meaningful information; no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, rich annotations, output schema present), the description fully covers what the agent needs: what data is returned (identity, team, role, etc.) and the prerequisite relationship to search_dota2_entities. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description essentially repeats the schema's parameter explanation ('exact canonical_title returned by search_dota2_entities'). It adds no new meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool retrieves 'player identity, current team, role, aliases, and team history' using a specific source. It clearly distinguishes from sibling tools like search_dota2_entities (search) and get_dota2_team (different resource).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies the required input is an 'exact Liquipedia canonical title returned by search_dota2_entities', implying a prerequisite and linking to the relevant sibling. It lacks explicit when-not-to-use or alternative scenarios but provides adequate guidance for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, fully covering the safety profile. The description adds value by specifying exactly what data is retrieved (metadata, roster, coaches), which annotations do not cover. No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence (15 words) that is front-loaded with the action and resource. Every word earns its place; there is no repetition or fluff. It is maximally concise while still being informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, output schema exists, rich annotations), the description covers the essential: what it returns, how to get the input, and the prerequisite. It omits details like rate limits or authentication, but those are not critical for a read-only, idempotent tool. The output schema handles return format, so completeness is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of canonical_title. The description reinforces the schema's message ('from an exact Liquipedia canonical title returned by search_dota2_entities') but does not add new details beyond that. Baseline of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('team metadata, roster, and coaches'), clearly distinguishing this tool from siblings like get_dota2_player or get_dota2_tournament. It also specifies the exact source (Liquipedia canonical title from search_dota2_entities), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description ties the tool directly to search_dota2_entities, implying that the agent should first obtain a canonical title via that search tool. This provides clear context for when to use this tool. However, it does not explicitly state when not to use it or mention alternatives, though the differentiation from sibling tools is clear from the scope.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this tool is read-only, idempotent, non-destructive, and open-world. The description adds useful context about what data is included (metadata, participants, placements) and explicitly excludes match loading. This extra behavioral detail beyond annotations is valuable, though the return format 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, zero wasted words. The first sentence states the purpose and input requirement, and the second sentence provides a critical exclusion and sibling tool alternative. Highly efficient for the information density.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 required parameter, no enums, simple input), high schema coverage (100%), and presence of an output schema, the description is complete. It covers what the tool returns, what it requires, and what it does not do, leaving no gaps for an AI agent to guess.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with only one parameter (canonical_title) already described as 'Exact canonical_title returned by search_dota2_entities.' The description reinforces that it must be an exact Liquipedia canonical title, which adds clarity beyond the schema. A baseline of 3 is appropriate, and the explicit linkage to search_dota2_entities earns a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies what the tool does: 'Get tournament metadata, participants, and placements' from a specific resource (Liquipedia canonical title). It also distinguishes itself from sibling tools by explicitly stating what it does not load (matches) and pointing to list_dota2_matches for that purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: when metadata, participants, and placements are needed from an exact canonical title. It also warns against using it for match data and directs to the alternative sibling tool list_dota2_matches for schedules or results.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, which the description complements by detailing that it returns results that may require user confirmation. There is no contradiction. The description adds behavioral context about requiring user confirmation for multiple candidates and its role as a precursor to detail tools, going slightly beyond annotation coverage. A near-perfect score is warranted as it adds value without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose, and every sentence adds value. No filler or redundant wording. It uses the available space efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (covering return format) and annotations adequately describe core behavioral traits (read-only, open-world, idempotent), the description is complete for the tool's complexity. It specifies the search source, when to use it, and a key caveat (user confirmation). Nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67%, meaning two of three parameters have descriptions in the schema: 'query' is described as 'Human-readable name or alias' and 'types' as 'Optional entity type filter.' The description adds general context around parameter usage (e.g., the intent of the tool), but is somewhat redundant with schema-level descriptions. With moderate schema coverage, the description provides minimal extra detail, so a 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches Liquipedia for Dota 2 tournaments, teams, or players, using a specific verb ('Search') and resource ('Liquipedia for Dota 2 entities'). It distinguishes itself from siblings by noting it is to be used before a 'detail tool' when an exact title is unknown, effectively differentiating from the get_dota2_* tools that retrieve specific entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('before a detail tool when an exact canonical title is not already known') and implies when not to use (when the exact title is known, use a detail tool instead). It also warns that multiple candidates require user confirmation, providing clear 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.
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