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schrodingers-boolean MCP — wraps StupidAPIs (requires X-API-Key)

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
pipeworx-io/mcp-schrodingers-boolean
GitHub Stars
0

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Tool DescriptionsA

Average 4.2/5 across 5 of 5 tools scored. Lowest: 3.5/5.

Server CoherenceA
Disambiguation4/5

Most tools have clearly distinct purposes: ask_pipeworx handles queries, discover_tools finds tools, and memory tools (forget, recall, remember) are self-contained. However, ask_pipeworx and discover_tools both involve tool discovery/selection, which could cause minor confusion about which to use for a given task.

Naming Consistency5/5

All tool names follow a consistent verb_pattern: 'ask_pipeworx', 'discover_tools', 'forget', 'recall', 'remember'. Naming is uniform and predictable.

Tool Count5/5

5 tools is well-scoped for a server that provides a natural language query interface, tool discovery, and memory management. Each tool earns its place without redundancy.

Completeness5/5

The tool set covers the core domain: querying (ask_pipeworx), tool discovery (discover_tools), and session memory (CRUD: remember, recall, forget). There are no obvious gaps for the stated purpose.

Available Tools

5 tools
ask_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".

ParametersJSON Schema
NameRequiredDescriptionDefault
questionYesYour question or request in natural language
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It explains the tool delegates to other tools (Pipeworx picks the right tool), but doesn't disclose rate limits, latency, or potential for errors. Sufficient for a natural language query tool.

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?

Three sentences, no fluff. First sentence states purpose, second explains behavior, third gives examples. Highly efficient.

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 the simple interface (one string param, no output schema), the description is nearly complete. It could mention that results are returned as plain text, but examples imply this. No major gaps.

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 coverage is 100% for the single parameter, and the description adds meaning by explaining the parameter is a natural language request with examples, going beyond the schema's minimal 'Your question or request in natural language'.

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 takes a plain English question and returns an answer from the best data source, with examples. It distinguishes from siblings like discover_tools by positioning itself as a unified query interface.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to just describe what you need without browsing tools or learning schemas, and provides three concrete examples. This is strong usage guidance.

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries")
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries the burden. It discloses that the tool is a search that 'returns the most relevant tools with names and descriptions,' which is sufficient. Missing details on whether it's read-only or has side effects, but the behavior is well implied.

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?

Two sentences that are front-loaded with purpose and immediate action, followed by a clear usage condition. No fluff; every sentence is meaningful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (2 params, no output schema, no nested objects) and no annotations, the description is complete. It explains purpose, when to use, and what the tool does, covering all essential aspects.

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?

Schema description coverage is 100%, so baseline is 3. The description adds context about the query format ('Natural language description of what you want to do') and default/max for limit, but these are already in schema. No extra semantics beyond schema.

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 ('Search') and resource ('Pipeworx tool catalog'), and specifies the purpose ('find the right tools for your task'). It effectively distinguishes from sibling tools, which focus on memory and boolean evaluation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Call this FIRST when you have 500+ tools available and need to find the right ones for your task.' This provides clear when-to-use guidance and implies alternatives (other tools) are for different tasks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

forgetAInspect

Delete a stored memory by key.

ParametersJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key to delete
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries the burden. It states the action is deletion but does not disclose side effects (e.g., whether deletion is permanent, if confirmation is needed, or if related memories are affected). Adequate but not rich.

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?

A single, concise sentence that directly conveys the purpose. No unnecessary words.

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 the tool's simplicity (one required parameter, no output schema), the description is functional but could add details like whether the key must exist or if deletion is reversible. Not inadequate but not comprehensive.

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?

Schema coverage is 100%, and the description mentions 'by key', which aligns with the schema's 'key' parameter. The schema already describes the parameter fully, so the description adds no new semantics beyond confirming the key is used for deletion.

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 action ('Delete'), the resource ('a stored memory'), and the mechanism ('by key'). It is unambiguous and distinguishes from siblings like 'recall' and 'remember'.

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 alternatives (e.g., when to delete vs. recall). No mention of prerequisites or conditions like key existence.

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must cover behavioral traits. Describes that omitting key lists all memories, which is useful. However, does not disclose any side effects (none expected), performance implications, or memory persistence details beyond 'session or previous sessions'.

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 two clear clauses covering both usage modes. No wasted words; front-loaded with purpose.

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, description could mention return format (e.g., string, JSON). However, for a simple key-value memory retrieval, the description is sufficient. The context about session persistence is helpful.

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 100% (parameter 'key' well described in schema). Description adds the key behavior (omit to list all), which adds value beyond schema. No additional parameters to explain.

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?

Clearly states the verb 'Retrieve' or 'list' and the resource 'memory by key', distinguishing the two modes (specific key vs all). This differentiates it from sibling tools like 'remember' (store) and 'forget' (delete).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to use this tool to retrieve context saved earlier, which implies it's for reading previously stored data. Does not explicitly mention when not to use or alternatives, but the context is clear.

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (e.g., "subject_property", "target_ticker", "user_preference")
valueYesValue to store (any text — findings, addresses, preferences, notes)
Behavior4/5

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 persistence differences between authenticated and anonymous users, which is helpful behavioral context beyond the input schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each adding distinct value: what it does, when to use it, and behavioral nuance. No wasted words.

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 and no annotations, the description adequately covers purpose, usage, and behavioral details. It could mention that the tool overwrites existing keys, but that is implied.

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?

Schema description coverage is 100%, so the schema already documents both parameters. The description does not add additional meaning beyond the schema, but the schema itself is clear.

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 'store' and resource 'key-value pair in session memory', and distinguishes its purpose from siblings like 'forget' and 'recall'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit use cases ('save intermediate findings, user preferences, or context across tool calls') but does not explicitly contrast with alternatives like 'forget' or 'recall'.

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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