Primo MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a distinct purpose: search, get details, cite, export, and suggest. No overlapping functionality.
Naming Consistency5/5All tool names follow a consistent 'primo_verb' pattern, making them predictable and easy to distinguish.
Tool Count5/55 tools cover the core library catalog operations without being excessive or insufficient.
Completeness5/5The set covers search, retrieval, citation, export, and suggestion, which are the key interactions for a library catalog.
Average 4/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository is licensed under MIT License.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not mention whether the tool is read-only, requires authentication, has rate limits, or makes external calls. The note about verifying citations implies potential inaccuracies but is insufficient.
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 concise and well-structured with clear Args and Returns sections. Every sentence serves a purpose, and the note about verification is valuable. No unnecessary information.
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?
While the description covers the core functionality, it lacks context about the tool's integration with Primo, limits on record IDs, or performance considerations. The presence of an output schema reduces the need to describe return values, but more guidance on usage context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains both parameters in the Args section: record IDs are 'Primo record IDs' and style lists five options with apa7 as default. This adds significant meaning beyond the schema's type and default values, especially given 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate formatted citations for library records.' It specifies inputs (record IDs and style) and output (formatted citations), and distinguishes from sibling tools like search, export, and suggest.
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 lacks guidance on when to use this tool versus alternatives like primo_search or primo_export. It does not mention prerequisites, context, or when not to use it. The note to verify citations hints at caution but does not provide usage rules.
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, the description should fully disclose behavioral traits. It describes the export operation and return format but does not mention that it is read-only, has no side effects, or any error handling behavior. The transparency is adequate for a simple export tool but could be improved.
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 very concise, using a structured docstring format with Args and Returns sections. Every sentence adds value, and there is no fluff. It is well-organized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, output schema present), the description covers purpose, parameters, and return value. However, it lacks information on error handling or prerequisites. Overall, it is fairly complete for a straightforward export tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add parameter meaning. It clearly explains both parameters: record_ids as a list of Primo record IDs and format with possible values and default. This adds value beyond the schema titles.
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 exports library records to reference manager formats. The verb 'Export' and resource 'library records' are specific. Although it does not explicitly differentiate from siblings like 'primo_search' or 'primo_cite', the purpose is distinct enough to be clear.
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 does not provide explicit guidance on when to use this tool versus alternatives. It only states what it does, leaving usage context implied. No exclusions or when-not-to-use scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It fails to disclose whether the operation is read-only, any side effects, authentication needs, or rate limits. It only describes parameter effects and return format.
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?
Well-structured with Args and Returns sections; every sentence adds value. The purpose is front-loaded, and the description is appropriately sized for the complexity (10 parameters).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description appropriately summarizes return content ('formatted search results with title, authors, year, identifiers, and availability'). It covers all necessary aspects for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description compensates fully by explaining every parameter's meaning and format (e.g., 'query: Search terms...', 'field: Search field -- any (default), title, creator...'). This adds significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
First sentence clearly states: 'Search the university library catalogue and subscribed databases.' This is a specific verb+resource, and it distinctly separates this tool from siblings like primo_cite or primo_export.
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?
Implied usage is clear from purpose, but there is no explicit guidance on when to use this tool versus alternatives, nor any 'when not to use' advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It states it returns full record details and lists included fields, which implies a read-only operation. However, it does not explicitly confirm safety (e.g., 'no side effects') or potential restrictions.
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 concise and well-structured: a brief purpose sentence, usage context, and clearly labeled Args/Returns sections. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description complements it by listing key return fields (title, authors, abstract, etc.). The tool is simple (single required parameter), and the description covers all needed context for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant context to the record_id parameter beyond the schema: it explains it comes from search results and provides examples (e.g., 'alma991234567890'). Schema coverage is 0%, so the description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get full details for a single library record.' It specifies the verb (Get), resource (library record), and scope (full details). It distinguishes from sibling tools like primo_search, which returns multiple records.
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 guidance on when to use: after primo_search, using the record ID. It includes an example format. However, it does not explicitly state when not to use or mention alternatives for similar tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the tool as getting suggestions (a read operation) and returns a list of terms. There is no mention of side effects, rate limits, or destructive actions, which is acceptable for an autocomplete tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with clear sections (Args and Returns). Every sentence adds value without redundancy. It is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema exists, the description is complete. It explains input and output sufficiently, leaving no ambiguity for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds significant value by explaining that 'query' is a partial search term and provides examples (e.g., 'entrepre'). This compensates for the lack of documentation in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets autocomplete suggestions for a search term, and distinguishes it from siblings like primo_search (full search) and primo_get_record (specific record retrieval). It lists specific uses: refining searches, checking subject headings, and exploring related terms.
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 explicitly states it is useful before running a full search, implying when to use it. While it does not explicitly state when not to use it or mention alternatives, the sibling tool 'primo_search' provides a clear contrast for full search scenarios.
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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- Evaluate tool definition quality.
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