LeetCode MCP Server

by AHM215

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: fetching problem text, generating templates, running/submitting code, retrieving daily challenge, getting full problem details, and searching. No two tools overlap in functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with underscores (e.g., fetch_problem_plain_text, run_code, submit_code). No mixing of styles.
Tool Count5/5
Seven tools is well-scoped for a LeetCode problem-solving assistant, covering essential operations from retrieval to submission without unnecessary extras.
Completeness4/5
The tool set covers core workflows: fetch, template, run, submit, search, and daily challenge. Minor gaps like user account management or submission history are absent but not critical for the primary use case.
Average 3.2/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not disclose side effects (e.g., submission quota, timeouts) or return format. Only states evaluation purpose.
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 with clear verb and target. No unnecessary words; front-loaded purpose.
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?
No output schema; missing parameter guidance and behavioral context. Barely adequate for 3-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%; description adds no parameter details. Required params (problem_slug, code_lang, code) lack format or constraints, leaving agent to guess.
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 (submits code) and the purpose (evaluation against full test suite), distinguishing it from run_code which likely runs sample tests. However, it could be more explicit about the difference.
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 on when to use this tool vs siblings like run_code. Does not mention prerequisites or alternative scenarios.
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 present, so the description carries the full burden. It does not explicitly state that the operation is read-only or idempotent, though the action 'retrieves' implies no side effects. The description is adequate but lacks explicit behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is reasonably concise, but it could be structured more effectively (e.g., listing key components) and still fits within acceptable length.
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?
With only one parameter and no output schema, the description should compensate by detailing the parameter and expected return value. It mentions 'related information' vaguely and does not specify what exactly is returned, leaving the agent uncertain.
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?
Schema description coverage is 0%, and the description does not explain the `titleSlug` parameter—what it represents, expected format, or how to obtain it. This is a significant gap given the single parameter.
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 retrieves details about a specific LeetCode problem including description, examples, constraints, and related information. However, it does not differentiate from the sibling tool `fetch_problem_plain_text`, which also retrieves a problem.
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 vs siblings like `fetch_problem_plain_text` or `search_problems`. It does not specify prerequisites or context for usage.
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 provided, so description carries full burden. It states 'returns the results' but does not disclose side effects (e.g., attempt tracking, rate limits, execution timeouts, error behavior). For a code execution tool, critical behavioral aspects are missing. Score 2.
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?
Single sentence is concise, but could be more structured (e.g., listing parameters). However, it's front-loaded with the action. Score 4 for being appropriately brief.
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 the tool's complexity (code execution, 3 params, no output schema, no annotations), the description is insufficient. It omits return format, error handling, language support, and execution context. Score 2 for being incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not explain what 'problem_slug', 'code_lang', or 'code' mean (e.g., valid code_lang values, code format). It adds no meaning beyond parameter names. Score 1 as it fails to compensate for missing schema descriptions.
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?
Clearly states 'Executes code against the example test cases' – verb (executes) and resource (code against example test cases) are specific. Differentiates from siblings like submit_code (which likely uses all test cases), though not explicitly. Score 4 because it's clear but no sibling differentiation.
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?
Implied usage: use this to test code against example cases before submission. But no explicit when-to-use, when-not-to-use, or alternative tools (e.g., 'Use this for quick testing; use submit_code for final submission'). Score 3 for implied but no explicit guidance.
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 exist, so the description carries full burden. It does not disclose any behavioral traits such as idempotency, rate limits, or error conditions. Only a basic fetch action is implied.
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 concise (13 words) and uses a single sentence. It efficiently conveys the core action, though it could be more informative.
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 one parameter and presence of an output schema, the description is minimally sufficient. However, it omits details about input format, error handling, and what 'plain text' means relative to the problem, which could affect agent understanding.
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 has 0% description coverage, leaving 'link' undefined. The description partially compensates by stating 'given its URL', but does not specify format (e.g., full URL vs slug) or required prefix.
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 verb 'Fetches' and the resource 'plain text content of a LeetCode problem', and specifies the input as a URL. However, it does not differentiate from sibling tool 'get_problem', which likely also fetches problem data.
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 on when to use this tool versus siblings like 'get_problem' or 'search_problems'. The description only states what it does, not when it is appropriate.
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 carries full responsibility for behavioral disclosure. The description only states what the tool does, but fails to reveal any behavioral traits such as whether it is a read-only operation, any side effects, authentication requirements, rate limits, or output format. For a template generation tool, one might assume it is safe, but the description does not confirm this.
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 of 12 words, extremely concise and structured to present the core function immediately. There is no extraneous information, and the sentence is front-loaded with the verb 'Generates' followed by the resource type. Every word contributes to understanding the tool's purpose.
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 that there is an output schema (though not provided), the description does not need to detail return values. However, the tool has two required parameters with no descriptions either in the schema or the description, and the description does not clarify what the generated template looks like. For example, does it include function signatures, imports, or comments? The description also does not relate the tool to the sibling tools (e.g., that it should be used before 'run_code'). It is minimally complete but leaves the user with unanswered questions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, meaning no parameter descriptions exist in the schema. The tool description does not add any semantic meaning to the parameters beyond mentioning them implicitly. It does not explain what constitutes a valid 'problem_slug' (e.g., format like 'two-sum') or 'code_lang' (e.g., 'python', 'java'). There are no examples or constraints, leaving the agent to guess the expected values.
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 tool 'generates a language-specific code template for a given LeetCode problem slug.' The verb 'generates' and the specific resource 'code template' combined with the inputs 'problem_slug' and 'code_lang' make the purpose unmistakable. It also distinguishes itself from siblings like 'run_code' or 'submit_code' which are execution actions, and 'fetch_problem_plain_text' which retrieves plain text, not a template.
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 explicit guidance on when to use this tool versus its alternatives. It does not mention prerequisites, context, or when not to use it. For example, it could have indicated that this is the first step before writing and submitting code, but it does not. With siblings that perform different tasks, the lack of usage direction is a notable gap.
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, the description carries the full burden. It mentions 'pagination support' but does not explain pagination mechanics, result ordering, or authentication requirements. It is adequate but lacks depth.
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, well-structured sentence of 20 words. It begins with the verb and key action, conveying essential information without redundancy.
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 6 parameters, no output schema, and no annotations, the description covers the filtering and pagination but omits the return format, result ordering, and authentication. It is incomplete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by naming filter categories (categories, tags, difficulty, keywords) that map to parameters. It adds meaning beyond the schema, though it could enumerate allowed values (e.g., difficulty levels).
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 tool's action ('Searches'), the resource ('LeetCode problems'), and the filtering criteria (categories, tags, difficulty, keywords) with pagination. It differentiates from siblings like get_problem which targets a single problem.
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 lacks any guidance on when to use this tool versus alternatives, such as recommending get_problem for specific problem lookups or generate_template for code generation. No exclusions or context are provided.
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?
With no annotations, the description carries full burden. It discloses the tool is a read operation ('Retrieves') and lists the returned content (description, constraints, examples). It does not mention potential side effects or rate limits, but the behavior is simple and adequately described.
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, clear sentence with no extraneous words. It is front-loaded with the purpose and provides essential detail about the return content.
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?
Given no output schema, the description explains return values ('problem description, constraints, and examples') which is sufficient for a simple retrieval tool. However, it lacks specificity about the exact structure or metadata elements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100%. According to guidelines, 0 params warrants a baseline of 4. The description adds no parameter info because none exist.
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 verb 'Retrieves', the resource 'today's LeetCode Daily Challenge problem', and specifies the scope ('today's') and content ('complete details, including problem description, constraints, and examples'). It effectively distinguishes from siblings like get_problem (for specific problems) and search_problems.
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 for retrieving today's challenge but provides no explicit guidance on when to use this tool versus alternatives (e.g., get_problem, search_problems). No when-not-to-use or exclusions are given.
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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