deckofcards
Server Details
Deck of Cards MCP — wraps deckofcardsapi.com (free, no auth)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-deckofcards
- GitHub Stars
- 0
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Usage analytics
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Tool Definition Quality
Average 3.8/5 across 4 of 4 tools scored.
Each tool has a clearly distinct purpose: discover_tools is for searching a catalog, new_deck creates a deck, draw_cards draws from it, and shuffle_deck reshuffles it. There is no overlap in functionality, making tool selection unambiguous for an agent.
Three tools (draw_cards, new_deck, shuffle_deck) follow a consistent verb_noun pattern, but discover_tools deviates slightly by using a verb that doesn't directly relate to card operations. The naming is mostly predictable and readable, with only minor inconsistency.
With 4 tools, the set is well-scoped for a card deck server. Each tool earns its place by covering essential operations: creating, drawing, shuffling, and a utility for tool discovery, which is appropriate for the domain.
The core card deck lifecycle is well-covered with create, draw, and shuffle operations. A minor gap exists in not having a tool to list or manage multiple decks, but agents can work around this with the provided tools for basic functionality.
Available Tools
8 toolsask_pipeworxAInspect
Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your question or request in natural language |
Tool Definition Quality
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 key behavioral traits: the tool automatically selects data sources and fills arguments, and it handles natural language queries. However, it lacks details on limitations (e.g., supported topics, error handling, rate limits) or response format, which are important for a tool with no 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by explanatory details and concrete examples. Every sentence earns its place by clarifying functionality or providing usage context without redundancy.
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 tool's complexity (natural language querying with automatic tool selection) and lack of annotations/output schema, the description is moderately complete. It explains the high-level behavior and provides examples, but does not cover potential constraints, error cases, or result formatting, leaving gaps for an agent to infer usage.
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 100%, with the 'question' parameter well-documented in the schema as 'Your question or request in natural language'. The description adds minimal value beyond this, only reinforcing that questions should be in 'plain English' with examples. Baseline 3 is appropriate since the schema does the heavy lifting.
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's purpose: 'Ask a question in plain English and get an answer from the best available data source.' It specifies the verb ('ask'), resource ('answer'), and mechanism ('Pipeworx picks the right tool, fills the arguments'). It distinguishes from siblings by emphasizing natural language input versus structured tool selection.
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 provides clear context on when to use this tool: for asking questions in plain English without needing to browse tools or learn schemas. It includes examples like 'What is the US trade deficit with China?' to illustrate appropriate use cases. However, it does not explicitly state when not to use it or name alternatives among sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discover_toolsAInspect
Search the Pipeworx tool catalog by describing what you need. Returns the most relevant tools with names and descriptions. Call this FIRST when you have 500+ tools available and need to find the right ones for your task.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of tools to return (default 20, max 50) | |
| query | Yes | Natural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries") |
Tool Definition Quality
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 key behavioral traits: it's a search operation (implying read-only), returns relevant tools with names/descriptions, and has a default/max limit context (implied by the input schema but not explicitly stated in the description). However, it doesn't mention error handling, rate limits, or authentication needs, leaving some gaps.
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 appropriately sized and front-loaded: the first sentence states the core purpose, the second adds critical usage guidance. Every sentence earns its place with no wasted words, making it highly efficient and easy to parse.
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 tool's moderate complexity (search function with 2 parameters), no annotations, and no output schema, the description is mostly complete. It covers purpose and usage well but lacks details on output format (beyond 'names and descriptions'), error cases, or performance expectations. It compensates somewhat with strong guidance.
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 100%, so the schema fully documents both parameters (query and limit). The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting, but no extra value is provided.
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's purpose with specific verbs ('Search the Pipeworx tool catalog') and resource ('tool catalog'), and distinguishes it from siblings by emphasizing its role in discovery when many tools are available. It explicitly mentions returning 'the most relevant tools with names and descriptions', making the outcome transparent.
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 provides explicit guidance on when to use this tool: 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This includes a specific condition (500+ tools) and timing (first), and it implicitly distinguishes from siblings by focusing on discovery rather than card/deck operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
draw_cardsAInspect
Draw cards from a deck. Returns card details (suit, value) and remaining count. Specify count to draw multiple cards at once.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of cards to draw. Defaults to 1. | |
| deck_id | Yes | The deck ID returned by new_deck (e.g. "3p40paa87x90"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the prerequisite (deck_id from new_deck), it doesn't describe what happens during the draw operation (e.g., cards are removed from deck, potential for empty deck, return format, error conditions). This leaves significant behavioral gaps.
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 sentences with zero waste. The first sentence states the purpose, the second provides essential usage guidance. Every word earns its place, and information is appropriately front-loaded.
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 mutation tool (drawing cards modifies deck state) with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, what happens to the deck after drawing, or potential edge cases (drawing more cards than available). The prerequisite mention helps but doesn't compensate for these gaps.
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 100%, so the schema already fully documents both parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples beyond the deck_id example already in schema). Baseline 3 is appropriate when schema does the heavy lifting.
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 specific action ('Draw one or more cards') and the resource ('from an existing deck'), distinguishing it from siblings like new_deck (creates deck) and shuffle_deck (reorders deck). It provides a complete verb+resource+scope statement.
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 when to use this tool ('Requires the deck_id returned by new_deck'), providing clear context about prerequisites. However, it doesn't specify when NOT to use it or mention alternatives like shuffle_deck for different operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
forgetCInspect
Delete a stored memory by key.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key to delete |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Delete' implies a destructive mutation, the description doesn't specify whether this operation is reversible, what permissions are required, or what happens on success/failure (e.g., error if key doesn't exist). It lacks critical behavioral details for a mutation tool.
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, efficient sentence that directly states the tool's function without any wasted words. It is appropriately sized and front-loaded, making it easy to parse quickly.
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 destructive mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like reversibility, error conditions, or response format, leaving significant gaps in understanding how to use the tool effectively.
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?
The schema description coverage is 100%, with the single parameter 'key' fully documented in the schema as 'Memory key to delete'. The description adds no additional meaning beyond this, such as format examples or constraints, but the schema provides adequate baseline coverage.
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 action ('Delete') and the resource ('a stored memory by key'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'recall' or 'remember' beyond the destructive nature implied by 'Delete'.
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 provides no guidance on when to use this tool versus alternatives like 'recall' or 'remember', nor does it mention prerequisites such as needing an existing memory key to delete. It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
new_deckAInspect
Create a shuffled deck of playing cards. Returns deck_id and remaining count. Use deck_count to combine multiple decks (e.g., 2 for 104 cards).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of standard 52-card decks to combine and shuffle. Defaults to 1. |
Tool Definition Quality
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 key behavioral traits: it creates and shuffles decks, returns a deck_id, and supports multiple decks via the count parameter. However, it lacks details on error conditions, rate limits, or whether the operation is idempotent, which would be helpful for a mutation tool.
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 appropriately sized and front-loaded, with two concise sentences that directly state the tool's action and outcome. Every sentence earns its place by covering creation, shuffling, deck count, and the return value without any waste.
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 tool's moderate complexity (a mutation with one parameter) and no annotations or output schema, the description is mostly complete. It covers the purpose, usage, and key behavior, but could improve by addressing potential errors or the format of the returned deck_id to fully compensate for the lack of structured data.
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?
The schema description coverage is 100%, so the input schema already documents the count parameter fully. The description adds minimal value by mentioning 'multiple decks' which aligns with the schema, but does not provide additional semantics beyond what the schema specifies, such as constraints or usage examples.
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's purpose with specific verbs ('create and shuffle') and resource ('new deck of playing cards'), and distinguishes it from sibling tools by mentioning it returns a deck_id for subsequent draws, which implies it's the initial deck creation tool versus draw_cards and shuffle_deck.
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 provides clear context for when to use this tool (to create and shuffle a new deck) and implicitly suggests alternatives by mentioning deck_id for subsequent draws, but does not explicitly state when not to use it or name specific alternatives like shuffle_deck for existing decks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recallAInspect
Retrieve a previously stored memory by key, or list all stored memories (omit key). Use this to retrieve context you saved earlier in the session or in previous sessions.
| Name | Required | Description | Default |
|---|---|---|---|
| key | No | Memory key to retrieve (omit to list all keys) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's behavior: retrieving or listing memories, with persistence across sessions. However, it lacks details on error handling (e.g., what happens if a key doesn't exist), performance traits (e.g., speed or limits), or response format. This leaves gaps in understanding how the tool behaves in edge cases.
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 concise and well-structured in two sentences. The first sentence clearly states the purpose and usage conditions, and the second provides context on when to use it. Every sentence earns its place without redundancy, making it front-loaded and efficient.
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 tool's moderate complexity (retrieval/listing with session persistence), no annotations, and no output schema, the description is somewhat complete but has gaps. It covers the basic purpose and usage but lacks details on return values, error cases, or behavioral constraints. This makes it adequate but not fully comprehensive for an agent to use confidently without additional context.
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?
The input schema has 100% description coverage, with the 'key' parameter documented as 'Memory key to retrieve (omit to list all keys).' The description adds minimal value beyond this, only reiterating the same semantics. Since schema coverage is high, the baseline is 3, and the description doesn't provide additional context like key format or examples, so it doesn't exceed the baseline.
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's purpose: 'Retrieve a previously stored memory by key, or list all stored memories (omit key).' It specifies the verb 'retrieve' and the resource 'memory,' and distinguishes between retrieval by key and listing all memories. However, it doesn't explicitly differentiate from sibling tools like 'remember' or 'forget,' which likely handle memory storage and deletion, so it's not a perfect 5.
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 provides clear context on when to use this tool: 'Use this to retrieve context you saved earlier in the session or in previous sessions.' It explains the condition for listing all memories ('omit key') and ties usage to retrieving saved context. However, it doesn't explicitly state when not to use it or name alternatives among siblings, such as 'remember' for storing memories, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rememberAInspect
Store a key-value pair in your session memory. Use this to save intermediate findings, user preferences, or context across tool calls. Authenticated users get persistent memory; anonymous sessions last 24 hours.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Memory key (e.g., "subject_property", "target_ticker", "user_preference") | |
| value | Yes | Value to store (any text — findings, addresses, preferences, notes) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly describes the storage action, persistence behavior (authenticated vs. anonymous), and session context, which are crucial for understanding how the tool behaves. However, it doesn't mention potential limitations like storage size, key uniqueness, or error conditions, leaving some behavioral aspects uncovered.
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 front-loaded with the core purpose in the first sentence, followed by usage guidance and behavioral details in the second. Every sentence adds value without redundancy, and it's appropriately sized for a tool with two parameters and no annotations, making it efficient and well-structured.
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 tool's complexity (simple storage with two parameters), no annotations, and no output schema, the description is largely complete. It covers purpose, usage, and key behavioral traits like persistence. However, it doesn't explain return values or error handling, which could be useful given the lack of output schema, leaving a minor gap in completeness.
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?
The schema description coverage is 100%, so the schema already fully documents both parameters (key and value). The description doesn't add any parameter-specific semantics beyond what's in the schema, such as format constraints or usage examples for the parameters. It meets the baseline for high schema coverage but doesn't provide extra value.
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 specific action ('Store a key-value pair') and resource ('in your session memory'), distinguishing it from siblings like 'recall' (retrieve) and 'forget' (delete). It provides concrete examples of what to store ('intermediate findings, user preferences, or context across tool calls'), making the purpose explicit and differentiated.
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 when to use this tool ('to save intermediate findings, user preferences, or context across tool calls') and provides context on persistence differences ('Authenticated users get persistent memory; anonymous sessions last 24 hours'), which helps guide usage decisions. It implicitly distinguishes from 'recall' (for retrieval) and 'forget' (for deletion) by focusing on storage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
shuffle_deckBInspect
Reshuffle a deck and reset all drawn cards back in. Returns updated remaining card count.
| Name | Required | Description | Default |
|---|---|---|---|
| deck_id | Yes | The deck ID to shuffle (e.g. "3p40paa87x90"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool shuffles a deck and returns drawn cards, which implies a mutation (reshuffling) and a resetting effect. However, it doesn't disclose key behavioral traits such as whether this requires specific permissions, if the shuffle is random or deterministic, what happens to the deck state (e.g., order changes), or any rate limits. For a mutation tool with zero annotation coverage, this is a significant gap.
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 appropriately sized and front-loaded, consisting of a single, efficient sentence: 'Shuffle (or re-shuffle) an existing deck, returning all drawn cards back into it.' Every word earns its place by conveying the action, target, and effect without redundancy or unnecessary detail.
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 tool's complexity (a mutation operation with no annotations and no output schema), the description is partially complete. It covers the basic purpose and effect but lacks details on behavioral aspects (e.g., permissions, shuffle randomness) and output (since no output schema exists). For a tool that modifies state, this leaves gaps in understanding how it behaves and what it returns, making it adequate but with clear room for improvement.
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?
The input schema has 100% description coverage, with the 'deck_id' parameter fully documented in the schema. The description does not add any meaning beyond what the schema provides (e.g., it doesn't explain the format of 'deck_id' further or provide usage examples). Since schema coverage is high, the baseline score is 3, as the description doesn't compensate but also doesn't detract.
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's purpose: 'Shuffle (or re-shuffle) an existing deck, returning all drawn cards back into it.' It specifies the verb ('shuffle') and resource ('an existing deck'), and distinguishes it from siblings by mentioning 'returning all drawn cards back into it,' which implies a resetting action not present in 'draw_cards' or 'new_deck.' However, it doesn't explicitly differentiate from 'new_deck' in terms of creating vs. modifying, which prevents a perfect score.
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 implies usage by specifying 'an existing deck,' suggesting it should be used on decks already created (likely via 'new_deck'), and 'returning all drawn cards back into it' hints it's useful after drawing cards (via 'draw_cards'). However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'new_deck' for a fresh shuffle or 'draw_cards' for drawing without shuffling), and no exclusions or prerequisites are stated.
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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