uooks
Server Details
Books MCP — wraps Open Library API (free, no auth)
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- pipeworx-io/mcp-books
- GitHub Stars
- 0
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Tool Definition Quality
Average 3.7/5 across 8 of 8 tools scored. Lowest: 2.9/5.
Most tools have distinct purposes, such as get_book for book details and search_books for book searches, but ask_pipeworx and discover_tools could cause confusion as both help find information, though ask_pipeworx is more direct while discover_tools is for tool discovery. The memory tools (remember, recall, forget) are clearly differentiated and do not overlap with others.
The naming is mixed with some tools using verb_noun patterns like get_book and search_books, while others like ask_pipeworx and discover_tools use verb_entity formats that are less consistent. The memory tools (remember, recall, forget) follow a clear verb-based pattern, but overall there is no uniform convention across all tools.
With 8 tools, the count is reasonable for a server that combines book data, memory management, and information retrieval. It's slightly broad in scope but manageable, as each tool serves a specific function without being overly sparse or bloated.
For the book domain, there is good coverage with search, get, and author tools, but lacks update or delete operations for books. The memory tools provide full CRUD (create, read, delete, with update implied via remember), but the information retrieval aspect (ask_pipeworx and discover_tools) feels like a separate domain with incomplete integration, leaving gaps in a unified workflow.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a query tool that interprets natural language, selects data sources automatically, and returns results. However, it doesn't mention potential limitations like response time, accuracy, or data source constraints, which would be helpful for a tool with no annotation coverage.
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 efficiently structured: it starts with the core functionality, explains the mechanism, provides usage guidance, and includes relevant examples. Every sentence adds value without redundancy, making it easy to understand quickly. The length is appropriate for a tool with this complexity.
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 processing, automatic tool selection) and lack of annotations or output schema, the description does a good job covering purpose, usage, and parameters. However, it doesn't detail output format or potential error conditions, which would help an agent handle responses better. It's mostly complete but has minor 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?
The schema description coverage is 100%, so the schema already documents the single 'question' parameter. The description adds value by explaining the parameter's semantics: it should be a 'question or request in natural language' and provides examples like 'Look up adverse events for ozempic'. This goes beyond the schema's basic description, earning a score above the baseline of 3.
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'), distinguishing it from sibling tools like search_books or discover_tools which have more specific scopes.
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: 'No need to browse tools or learn schemas — just describe what you need.' It provides clear alternatives (implicitly, use other tools if you want to browse or learn schemas) and includes concrete examples like 'What is the US trade deficit with China?' to illustrate appropriate use cases.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it's a search operation that returns relevant tools based on natural language queries, with implied read-only functionality. However, it doesn't mention potential limitations like rate limits, authentication requirements, or error conditions that would be helpful for a discovery 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 perfectly concise with two sentences that each serve distinct purposes: the first explains what the tool does, and the second provides crucial usage guidance. There's no wasted language, and the most important information (to call this first in specific scenarios) 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?
Given the tool's moderate complexity (search functionality with natural language queries) and the absence of both annotations and output schema, the description does a good job of explaining the tool's purpose and primary use case. However, it doesn't describe what the output looks like (beyond mentioning it returns 'tools with names and descriptions'), which would be helpful since there's no output schema provided.
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 has 100% description coverage, so the parameters are well-documented in the structured schema. The description doesn't add significant semantic value beyond what's already in the schema descriptions, though it reinforces the natural language query concept. This meets the baseline expectation when schema coverage is high.
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', 'returns') and resources ('Pipeworx tool catalog', 'most relevant tools with names and descriptions'). It explicitly distinguishes this from sibling tools by emphasizing its role in discovering tools rather than directly accessing specific resources like authors or books.
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') and includes a clear alternative scenario (when you don't have many tools or already know which ones to use). This gives strong contextual direction for tool selection.
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. It states 'Delete', implying a destructive mutation, but doesn't disclose behavioral traits like whether deletion is permanent, requires specific permissions, has side effects, or provides confirmation. This is a significant gap for a mutation tool with zero annotation coverage.
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 with zero waste. It's front-loaded with the core action ('Delete'), making it easy to parse quickly, which is ideal for concise tool definitions.
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 as a destructive operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., permanence, permissions) and what happens post-deletion (e.g., success confirmation or error handling), which are crucial for safe and effective use.
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 delete'. The description adds no additional meaning beyond this, such as key format or examples. With high schema coverage, the baseline is 3, as 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 action ('Delete') and the resource ('a stored memory by key'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'recall' or 'remember', which likely handle memory retrieval and storage respectively, so it misses full sibling distinction.
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. It doesn't mention prerequisites, such as needing an existing memory key, or contrast with tools like 'recall' (which might retrieve memories) or 'remember' (which might store them), leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_authorAInspect
Get author biography, major works, and key information using their Open Library ID (e.g., "OL23919A"). Returns birth/death dates, complete bibliography, and biographical summary.
| Name | Required | Description | Default |
|---|---|---|---|
| author_key | Yes | Open Library author key (e.g., OL23919A) |
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 retrieves information ('Get biography and key info'), which implies a read-only operation, but it does not disclose any behavioral traits such as rate limits, error handling, or response format. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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 front-loads the core purpose and includes necessary details (the parameter and an example) without any wasted words. It is appropriately sized for a simple tool with one parameter, making it easy to understand 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?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameter usage, but lacks details on behavioral aspects like response format or error conditions. For a read-only tool with no annotations, more context would be beneficial to fully guide an agent.
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 parameter 'author_key' fully documented in the input schema. The description adds minimal value by reiterating the parameter's purpose and providing an example ('e.g., OL23919A'), but it does not offer additional semantics beyond what the schema already provides. This meets the baseline for high schema 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 specific action ('Get biography and key info') and the resource ('for an author'), distinguishing it from sibling tools like 'get_book' and 'search_books'. It explicitly mentions the required identifier ('Open Library author key'), making the purpose unambiguous and distinct.
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 the required parameter ('using their Open Library author key'), but it does not explicitly state when to use this tool versus alternatives like 'get_book' or 'search_books'. There is no guidance on exclusions or prerequisites, leaving the context somewhat open-ended.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_bookBInspect
Get full details for a book by ISBN. Returns title, author, publication date, description, ratings, and availability status.
| Name | Required | Description | Default |
|---|---|---|---|
| isbn | Yes | ISBN-10 or ISBN-13 |
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 states the action ('Get full details') but doesn't cover critical aspects like whether this is a read-only operation, potential error conditions (e.g., invalid ISBN), rate limits, or authentication needs. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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 purpose without any wasted words. It is front-loaded and appropriately sized for a simple tool, earning the highest score for conciseness.
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 low complexity (one parameter, no output schema, no annotations), the description is minimally adequate but incomplete. It covers the basic purpose but lacks details on usage guidelines, behavioral traits, and output expectations, which are necessary for effective agent operation despite the simple 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 schema description coverage is 100%, with the parameter 'isbn' fully documented in the schema as 'ISBN-10 or ISBN-13'. The description adds no additional meaning beyond this, such as format examples or edge cases, so it meets the baseline score for high schema coverage without 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 verb ('Get') and resource ('full details for a book'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_books' (which might return multiple results) or 'get_author' (which targets a different resource), so it doesn't reach the highest 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 provides no guidance on when to use this tool versus alternatives such as 'search_books' or 'get_author'. It lacks context about prerequisites, exclusions, or specific scenarios for usage, leaving the agent with minimal direction.
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. It discloses that the tool can retrieve or list memories, including cross-session persistence, but lacks details on error handling (e.g., if key doesn't exist), permissions, rate limits, or return format. It adds some behavioral context but is incomplete for a tool with no annotation coverage.
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 two sentences with zero waste: the first states the purpose and parameter usage, the second provides usage context. It's front-loaded and efficiently structured, with every sentence earning its place.
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 no annotations and no output schema, the description is moderately complete for a simple retrieval tool. It covers the basic purpose and parameter behavior but lacks details on return values, error cases, or limitations. It's adequate but has clear gaps in behavioral transparency.
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 documents the optional 'key' parameter. The description adds value by explaining the semantics: omitting the key lists all memories, and the key retrieves a specific memory. This clarifies the dual functionality beyond the schema's basic description.
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'/'list') and resource ('memory'), though it doesn't explicitly differentiate from sibling tools like 'remember' or 'forget' beyond mentioning 'saved earlier.'
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 the tool: 'Use this to retrieve context you saved earlier in the session or in previous sessions.' It explains the behavior when the key is omitted (list all keys), but it doesn't explicitly mention when not to use it or name alternatives among siblings.
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 effectively describes key behavioral traits: the tool performs a write operation (implied by 'store'), specifies persistence differences for authenticated vs. anonymous users, and mentions the 24-hour limit for anonymous sessions. However, it does not cover potential rate limits, error conditions, or response formats.
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 sentences that efficiently convey purpose, usage, and behavioral details without redundancy. Every sentence adds value, and there is no wasted text, making it highly concise 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 moderate complexity (write operation with persistence rules), no annotations, and no output schema, the description is mostly complete. It covers purpose, usage, and key behavioral aspects like persistence differences, but lacks details on return values, error handling, or specific constraints, leaving minor 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?
The schema description coverage is 100%, so the input schema already fully documents the 'key' and 'value' parameters. The description does not add any additional semantic information about parameters beyond what the schema provides, such as constraints or usage nuances, meeting the baseline for high schema 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 tool's purpose with specific verbs ('store a key-value pair') and resource ('in your session memory'), distinguishing it from sibling tools like 'recall' (likely for retrieval) and 'forget' (likely for deletion). It specifies the storage mechanism and typical use cases, making the purpose unambiguous.
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 save intermediate findings, user preferences, or context across tool calls'), but does not explicitly mention when not to use it or name alternatives. It distinguishes from siblings by function but lacks explicit exclusions or comparisons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_booksBInspect
Search for books by title, author, or keyword. Returns title, author, year, ISBN, and cover image URL. Use this to discover books before fetching full details.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results to return (1-20, default 5) | |
| query | Yes | Search query (title, author, or keywords) |
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 mentions the return fields (title, author, year, ISBN, cover image URL), which adds value beyond the input schema. However, it doesn't cover critical behaviors like pagination (implied by 'limit' parameter but not explained), error handling, rate limits, or authentication needs. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 highly concise and front-loaded, consisting of two sentences that efficiently convey the tool's purpose and return values. Every sentence earns its place by providing essential information without redundancy or fluff, making it easy for an agent 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?
Given the tool's moderate complexity (search functionality with 2 parameters) and lack of annotations or output schema, the description is partially complete. It covers the basic purpose and return fields, but misses details on behavioral aspects like result ordering, pagination, or error cases. Without an output schema, the description should ideally explain the return structure more thoroughly, but it does list key fields, providing a minimal foundation.
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 description adds minimal parameter semantics beyond the input schema, which has 100% coverage. It mentions search criteria ('by title, author, or keyword') that aligns with the 'query' parameter's schema description, but doesn't provide additional context like search syntax or ranking. Since the schema already documents both parameters thoroughly, the description meets the baseline without compensating for any gaps.
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 for books') and resources ('books'), and specifies search criteria ('by title, author, or keyword'). It distinguishes from sibling tools like 'get_author' and 'get_book' by focusing on search functionality rather than direct retrieval. However, it doesn't explicitly contrast with siblings beyond implying different use cases.
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 context through the search criteria, suggesting it's for finding books based on textual queries. However, it lacks explicit guidance on when to use this tool versus alternatives like 'get_book' (which might retrieve a specific book by ID) or 'get_author'. No exclusions or prerequisites are mentioned, leaving usage decisions to inference.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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