AtCoder MCP Server
Server Details
Search AtCoder problems and fetch public problem statements through MCP.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- ketherworks/atcoder-mcp-server
- GitHub Stars
- 0
- Server Listing
- atcoder-mcp-server
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.3/5 across 4 of 4 tools scored.
Each tool has a clearly distinct role: capabilities reports meta-info, fetch_problem retrieves problem statements, health checks status, and search_problems resolves identifiers. No functional overlap.
All tools share the 'oj_' prefix, but the verb/noun pattern varies: 'fetch_problem' and 'search_problems' are verb_noun, while 'capabilities' and 'health' are nouns. The prefix ensures cohesion, though the pattern is not perfectly uniform.
With only 4 tools, the server is tightly scoped to a read-only problem surface. The count feels sufficient for the advertised purpose of fetching problems and checking capabilities.
The server explicitly states it only supports an audited read surface, and capabilities documents unsupported operations. The tools cover the stated domain (fetch, search, health, meta), with no obvious gaps for that limited scope.
Available Tools
4 toolsoj_capabilitiesAtCoder Provider CapabilitiesARead-onlyIdempotentInspect
Report the audited anonymous AtCoder read surface and explicitly unsupported operations.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, idempotentHint=true, destructiveHint=false. The description adds context about the tool being 'audited' and 'anonymous', which goes beyond annotations and clarifies behavioral traits.
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, well-structured sentence that is front-loaded and contains no unnecessary words.
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?
Given zero parameters, rich annotations, and an output schema, the description is sufficiently complete. It clearly explains the tool's purpose without needing additional details.
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?
No parameters exist, so baseline score is 4. The description adds no parameter information, which is appropriate since there are none.
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 the specific verb 'report' and resource 'capabilities', clearly stating it reports audited anonymous read surface and unsupported operations. It distinguishes from sibling tools like oj_fetch_problem, oj_health, and oj_search_problems.
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 implicitly indicates usage for discovering capabilities but does not explicitly state when to use this tool versus alternatives or provide when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
oj_fetch_problemFetch AtCoder ProblemARead-onlyIdempotentInspect
Fetch one public problem statement from an exact contest/task pair or canonical atcoder.jp task URL. Returns sanitized HTML with preserved math, samples, limits, hashes, and source provenance.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already signal safety (readOnly, idempotent). The description adds value by detailing output content (sanitized HTML with math, samples, limits, hashes, provenance), expanding beyond annotation hints.
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, well-structured sentence that front-loads the purpose and is free of redundant words.
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?
With a clear description, full schema coverage, and annotations, the tool definition feels complete. The output schema (not shown) is referenced, and the description covers necessary return details.
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 coverage is 100%, so baseline 3 applies. The description reiterates parameter roles ('exact contest/task pair or URL') but adds no semantic detail beyond the schema.
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 clearly states the tool fetches one public problem statement using an exact contest/task pair or URL. It distinctly separates from sibling tools like oj_search_problems by specifying exact identification.
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?
No explicit guidance on when to use or not use this tool over alternatives is provided. While siblings are listed, the description doesn't contrast usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
oj_healthAtCoder Provider HealthARead-onlyIdempotentInspect
Report local readiness and the latest observed AtCoder page-read status without probing upstream.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and idempotent. The description adds that it uses local observations ('latest observed') and avoids upstream probes, which is helpful behavioral context beyond the 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, clear sentence of 13 words with no fluff. Every word is necessary and contributes to understanding.
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 zero-parameter tool with an output schema, the description completely and accurately captures the tool's purpose and behavior. No gaps remain.
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?
No parameters exist, and schema coverage is 100%. The description provides context about what is reported (local readiness and observed status), adding value beyond the empty schema.
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 clearly states the tool reports 'local readiness' and 'latest observed AtCoder page-read status', which distinguishes it from siblings like oj_capabilities (lists capabilities) and oj_search_problems (searches problems).
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 phrase 'without probing upstream' implies lightweight usage, but the description does not explicitly state when to use this tool versus alternatives. It is clear enough for an agent to infer its role as a health check.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
oj_search_problemsFind Exact AtCoder ProblemARead-onlyIdempotentInspect
Resolve exactly one contest/task id, atcoder:contest/task id, or canonical task URL. Free-text and catalog crawling are not supported.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | Yes | ||
| query | Yes | ||
| locale | No | ||
| platform | Yes | ||
| requestId | Yes | ||
| schemaVersion | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds behavioral context by specifying the exact input format (contest/task id, etc.), which goes beyond annotations. However, it does not describe the return behavior in detail, but the output schema compensates.
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?
Two short sentences, front-loaded with the action verb 'Resolve', and no wasted words. Every sentence adds essential information: what inputs are valid and what is not supported.
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?
Given the presence of an output schema and annotations, the description is adequate for core behavior but lacks explanation for several parameters (limit, locale) and does not mention the output's nature. This leaves minor gaps, though the output schema mitigates the return value issue.
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 0%, so the description must explain parameters. It only addresses the query parameter (describing accepted formats) but leaves limit, locale, and others undocumented. This partial coverage is insufficient for an agent to correctly set all parameters.
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 clearly states that the tool resolves exact contest/task IDs, AtCoder-specific IDs, or canonical URLs, and explicitly distinguishes it from free-text or catalog crawling. This specificity, combined with the resource 'contest/task id', makes the purpose unambiguous and differentiates it from sibling tools like oj_fetch_problem.
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 explicitly states that free-text and catalog crawling are not supported, providing clear guidance on when not to use the tool. While it does not directly name alternatives, the context of sibling tools and the limitation to exact identifiers gives strong usage context.
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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