CTFd MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: challenge_details retrieves metadata, list_challenges provides a filtered list, start_container initiates a container, stop_container terminates one, and submit_flag handles flag submission. The descriptions clearly differentiate these operations, making misselection unlikely.
Naming Consistency5/5All tools follow a consistent verb_noun pattern (e.g., list_challenges, start_container, submit_flag) with clear, descriptive names. There are no deviations in style or convention, making the set predictable and easy to understand.
Tool Count5/5With 5 tools, this server is well-scoped for CTF (Capture The Flag) management. Each tool serves a specific, essential function in the challenge lifecycle—from browsing and starting challenges to submitting flags—without unnecessary bloat or gaps.
Completeness4/5The toolset covers core CTF workflows: listing and viewing challenges, managing containers, and flag submission. A minor gap exists in operations like updating challenge details or managing user accounts, but agents can likely work around this for basic CTF participation.
Average 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
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- Last stable release on
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- No high-severity vulnerability alerts
- No code scanning findings
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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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description provides no behavioral details. It does not disclose whether flag submission is idempotent, what the side effects are (e.g., scoring), or any error conditions. The agent has no insight into tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but fails to convey necessary information. While brevity is valued, this description is under-specified and does not earn its place as an informative guide for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, output schema, and parameter descriptions, the description is completely inadequate. It does not provide enough context for the agent to know when to use the tool, what the return value looks like, or how it fits into the challenge lifecycle.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning beyond the property names. It does not explain what 'flag' format is expected, how to obtain challenge_id, or any constraints like case sensitivity. The description fails to compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (submit) and resource (flag for a challenge ID). It is specific enough to distinguish from sibling tools like list_challenges and start_container, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool, any prerequisites (e.g., must have a started container), or when to avoid it. No alternatives are listed compared to siblings.
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 the description must carry behavioral disclosure. It fails to state whether stopping is destructive, requires authentication, or what the effect is. The mention of different systems hints at behavior but lacks detail.
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?
Single sentence with no extraneous words. Front-loaded with the action 'Unified stop'. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lacks details on return values, errors, prerequisites, or side effects. No output schema and minimal description make it insufficient for a complete understanding.
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?
With 0% schema description coverage, the description adds partial meaning by linking parameters to systems (whale vs. ctfd-owl/k8s). However, it doesn't explain the parameters fully (e.g., format, requiredness beyond default null).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Unified stop', clearly indicating the tool stops containers. It differentiates from sibling 'start_container' by being the inverse operation. However, it does not specify a single verb+resource but rather describes two possible use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'start_container' or when not to use it. The only usage hint is about choosing parameters based on system, which is implicit.
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. Description implies read-only but lacks details on authentication, rate limits, or other behavioral traits beyond listing.
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?
One sentence front-loaded with purpose, followed by optional filters. No redundancy.
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?
Lacks output schema or description of return structure (e.g., array of challenge objects, pagination). Adequate for a simple list but leaves ambiguity for an AI agent.
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?
Schema coverage is 0% (no param descriptions). The description mentions optional filtering by category and unsolved status but does not clarify valid category values or the precise meaning of 'unsolved only' (e.g., user-specific unsolved).
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 visible challenges with optional filters, distinguishing it from siblings like challenge_details or submit_flag.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as challenge_details for individual challenge details or submit_flag for flag submission.
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 burden. It mentions plugin detection behavior but does not disclose what happens on failure, permissions, or consequences beyond starting.
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, front-loaded with key action and plugin detection, and contains no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description omits crucial details such as return values, side effects, prerequisites (e.g., challenge existence), and error conditions, making it incomplete for a start action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single required parameter 'challenge_id' has 0% schema description coverage, and the description does not explain its meaning, format, or how to obtain it, leaving the agent without guidance.
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?
Description clearly states the verb 'start' and resource 'container', and explicitly mentions unified detection of plugins (whale, ctfd-owl, k8s), distinguishing it from sibling tools like stop_container.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating it is a unified start, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or context.
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 must disclose behavioral traits. It implies a read-only get operation, but does not explicitly state side effects, authentication, or error handling. Minimal but adequate for a simple fetch.
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?
Single sentence with parenthetical is extremely concise and front-loaded. No unnecessary words.
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?
Given the tool's simplicity (1 param, no output schema), the description is adequate but could specify the return format (e.g., JSON structure) or that it returns all details. Slightly lacking for complete understanding.
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?
Schema coverage is 0%, so description should compensate. It does not explain challenge_id beyond its name and type; omits where to obtain the ID (e.g., from list_challenges). Fails to add value over the schema.
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 retrieves challenge details by ID, specifying the fields (description, files, meta). It distinguishes from sibling tools like list_challenges, which likely lists all challenges.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this versus alternatives like list_challenges. The purpose is implied, but no when-not or prerequisite mentioned.
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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