mcp-open-library
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
The tools are mostly distinct, with clear separation between author-related and book-related operations. However, 'get_author_info' and 'get_authors_by_name' could cause minor confusion as both retrieve author information, though one is for a specific author and the other for searching by name. The other tools have well-defined, non-overlapping purposes.
Naming Consistency5/5All tool names follow a consistent 'verb_noun' pattern with snake_case, such as 'get_author_info' and 'get_book_by_title'. The naming is predictable and readable throughout the set, with no deviations in style or convention.
Tool Count5/5With 6 tools, this server is well-scoped for its purpose of querying Open Library data. Each tool serves a specific function (e.g., retrieving author info, book details, covers), and the count is reasonable without being too sparse or overwhelming for the domain.
Completeness3/5The tool set covers basic read operations for authors and books, including search and retrieval of details and images. However, there are notable gaps, such as the lack of update, delete, or creation tools (e.g., for managing user data or book lists), which limits it to read-only access and may not support full workflows in the library domain.
Average 3.3/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 2 community issues answered or closed in the last 6 months
- 22 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 8 times in the last 30 days.
This repository includes a glama.json configuration file.
This server has been verified by its author.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool is for searching, implying it's a read operation, but lacks details on permissions, rate limits, response format, or error handling. This is a significant gap 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'author information' includes, how results are returned, or any limitations, leaving gaps in understanding the tool's behavior and output.
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?
The schema description coverage is 100%, so the schema already documents the single parameter 'name'. The description adds no additional meaning beyond what the schema provides, such as search behavior or result details, 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Search for author information on Open Library.' It specifies the verb ('search') and resource ('author information'), though it doesn't explicitly differentiate from sibling tools like 'get_author_info' or 'get_author_photo'.
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 is provided on when to use this tool versus alternatives. The description doesn't mention sibling tools or specify use cases, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information' but does not specify what that includes (e.g., title, author, publication year), whether it's a read-only operation, potential error conditions, or rate limits. This leaves significant gaps in understanding the tool's behavior.
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, efficient sentence that directly states the tool's purpose and key input mechanism. It is front-loaded with essential information and contains no redundant or unnecessary details.
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?
Given the lack of annotations and output schema, the description is insufficient for a tool that retrieves 'detailed information'. It does not clarify what data is returned, potential limitations, or how to handle errors, leaving the agent with incomplete context for effective use.
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?
The schema description coverage is 100%, with clear descriptions for both parameters, including an enum for 'idType'. The description adds minimal value by listing the identifier types in parentheses, but it does not provide additional context such as format examples or constraints beyond what the schema already documents.
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 tool's purpose with a specific verb ('Get') and resource ('detailed information about a book'), and it specifies the mechanism ('using its identifier'). However, it does not explicitly differentiate from sibling tools like 'get_book_by_title', which serves a similar purpose but uses a different lookup method.
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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'get_book_by_title' for title-based lookups or 'get_author_info' for author-related queries, nor does it specify any prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it states what the tool does (gets a URL), it doesn't describe important behavioral aspects: whether this requires authentication, rate limits, what happens with invalid identifiers, if the URL is permanent or temporary, or what format the URL returns (e.g., direct image link vs. API endpoint). For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a straightforward tool and front-loads the essential information. Every element of the sentence serves a purpose, making it an excellent example of conciseness.
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 moderate complexity (3 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameters but lacks behavioral context and usage guidance. Without annotations or output schema, the description should ideally provide more about what the URL looks like, error conditions, or typical use cases to be fully complete for agent 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?
The description mentions 'using a key (ISBN, OCLC, LCCN, OLID, ID) and value,' which aligns with the schema's 'key' and 'value' parameters. However, with 100% schema description coverage, the schema already fully documents all three parameters including their enums and descriptions. The description adds minimal value beyond what's in the structured schema, 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.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get the URL for a book's cover image') and resource ('book's cover image'), which is specific and unambiguous. It distinguishes itself from sibling tools like 'get_book_by_id' or 'get_book_by_title' by focusing specifically on cover images rather than book metadata. However, it doesn't explicitly contrast with 'get_author_photo' or other image-related tools, preventing 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.
Usage Guidelines2/5Does 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 when this tool is appropriate compared to sibling tools like 'get_book_by_id' (which might also return cover information) or 'get_author_photo' (for author images). There's no context about prerequisites, limitations, or typical use cases for cover images versus other book data.
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?
With no annotations provided, the description carries full burden but only states it's a search operation. It doesn't disclose behavioral traits like whether it returns multiple matches, handles partial titles, requires authentication, has rate limits, or what happens on no results. This leaves significant gaps for a 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without redundancy. It's 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a search tool that likely returns complex data, the description is incomplete. It doesn't explain return values, error handling, or behavioral nuances, leaving the agent with insufficient context to use the tool effectively beyond basic invocation.
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?
The schema description coverage is 100%, with the parameter 'title' fully documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, such as format examples or search behavior details. Baseline 3 is appropriate when the schema does the heavy lifting.
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 ('Search for a book') and resource ('on Open Library'), with the specific criterion 'by its title' distinguishing it from sibling tools like get_book_by_id. However, it doesn't explicitly differentiate from get_authors_by_name or other search tools, keeping it from 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.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when searching by title rather than ID or author name, but doesn't explicitly state when to use this tool versus alternatives like get_book_by_id or get_authors_by_name. No guidance on prerequisites, error conditions, or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns a URL, which is useful, but lacks details on error handling (e.g., if the OLID is invalid), rate limits, authentication needs, or whether the operation is read-only (implied but not explicit). This is a significant gap 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key action ('Get the URL') and includes essential context (resource and input). There is zero waste, and every word earns its place, 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.
Completeness3/5Given 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 input, but lacks behavioral details (e.g., error cases) and output specifics (though no output schema exists, it could hint at the URL format). This meets minimum viability with clear gaps.
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?
Schema description coverage is 100%, with the parameter 'olid' fully documented in the schema (including type and example). The description adds minimal value beyond the schema by mentioning the OLID in context, but does not provide additional syntax or format details. Baseline 3 is appropriate 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get the URL') and resource ('an author's photo'), using the exact verb 'Get'. It distinguishes this tool from siblings like 'get_author_info' (which likely returns metadata) and 'get_book_cover' (which targets books), making the purpose unambiguous and sibling-differentiated.
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 specifying the required input ('using their Open Library Author ID'), which suggests when to use this tool (when you have an OLID). However, it does not explicitly state when not to use it or name alternatives (e.g., vs. 'get_author_info' for non-photo data), leaving some guidance gaps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It specifies the required input format (Open Library Author Key) and implies a read-only operation ('Get'), but doesn't describe potential errors (e.g., invalid keys), rate limits, authentication needs, or the structure/format of the returned information. It adds basic context but lacks richer behavioral details.
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, well-structured sentence that front-loads the core purpose and efficiently includes the key constraint (using the Open Library Author Key) with a helpful example. Every word earns its place with zero waste.
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 low complexity (single parameter, no output schema, no annotations), the description is adequate but has gaps. It covers the purpose and input requirement clearly, but without annotations or output schema, it doesn't address behavioral aspects like error handling or return format, leaving the agent with incomplete context for reliable use.
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?
Schema description coverage is 100%, so the schema already fully documents the single parameter 'author_key' with its description and type. The description adds minimal value by restating the parameter's purpose and providing an example (OL23919A), but doesn't go beyond what the schema provides in terms of semantics or constraints.
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 specific action ('Get detailed information') and target resource ('for a specific author'), using a precise verb+resource combination. It distinguishes this tool from siblings like 'get_author_photo' (which retrieves photos) and 'get_authors_by_name' (which searches by name rather than key).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does 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: when you have an Open Library Author Key and need detailed author information. It implicitly suggests alternatives (e.g., use 'get_authors_by_name' if you don't have a key), but doesn't explicitly state when not to use it or name alternatives directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/8enSmith/mcp-open-library'
If you have feedback or need assistance with the MCP directory API, please join our Discord server