life-science-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool serves a distinct purpose: searching for tools, retrieving schema details, and executing tools. There is no overlap between these operations.
Naming Consistency5/5All tool names follow a consistent verb-noun camelCase pattern: searchTools, getToolInfo, callTool. The naming is uniform and predictable.
Tool Count5/5With only 3 tools, the server is minimal yet appropriately scoped for its role as a meta-server. It provides the essential discover, inspect, and execute operations without unnecessary bloat.
Completeness5/5The server covers the full lifecycle for interacting with external life science tools: discover via search, understand via getToolInfo, and run via callTool. No obvious gaps in this proxy-like design.
Average 3/5 across 3 of 3 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
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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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavior disclosure. It only says 'execute a tool' and omits side effects, auth requirements, error behavior, whether execution is remote, and what a successful call returns. This is effectively a placeholder for behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. It is concise, but the brevity comes at the cost of substance; there is room to add a second sentence clarifying source/tool meanings without hurting clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter tool with no annotations and no output schema, a one-sentence description is far from complete. It leaves unclear how to populate params, where to get valid source/tool values, what the response looks like, and how this tool fits the workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate for the bare string/object types. It adds only the weak hint that 'source' is a life science source and 'tool' is the thing being executed; the required params object and accepted values/formats are completely unspecified.
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 states a concrete action (execute) and a resource (a tool on a life science source), and the contrast with siblings searchTools/getToolInfo suggests this is the invocation sibling. However, it doesn't explain what constitutes a tool, so the purpose is clear but not fully elaborated.
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 given on when to choose callTool over searchTools or getToolInfo, nor any prerequisite such as discovering valid source/tool names. The context signals list siblings, but the description itself provides no routing or exclusions.
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 only states the get-like behavior and does not mention whether the operation is strictly read-only, how missing or invalid source/tool values behave, or what the returned schema looks like.
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?
A single front-loaded sentence with no filler. Every word contributes to understanding the tool's scope, and the structure wastes no space.
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 0% parameter documentation, the description is too thin. An agent is left to guess what a 'source' is, how to find valid source/tool identifiers, and how this tool fits into the search-then-call workflow suggested by the sibling names.
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 0%, but the phrase 'for a specific tool on a source' gives meaning to the two string parameters tool and source. It adds some value beyond the raw schema, yet it does not explain acceptable formats, where valid source identifiers come from, or how tool names should be specified.
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?
States a specific verb ('get') and resource ('full parameter schema for a specific tool on a source'), which clearly conveys what the tool does. It is distinguishable from siblings searchTools and callTool, though it does not explicitly name them.
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?
No explicit when-to-use or when-not-to-use guidance is provided. The intended usage can be inferred from the sibling names: use this to inspect a tool's schema before calling it, but that is implied rather than stated.
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. It only states that the tool searches, but does not reveal what the search returns, whether it is read-only, any rate limits, authentication needs, or scope limitations. This is a significant transparency gap.
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, front-loaded sentence that conveys the essential purpose with no filler. Every word contributes to understanding the tool's function.
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 output schema, no annotations, and 0% schema description coverage, the description is under-specified. It fails to explain return values, parameter details, edge cases, or usage context, leaving an agent with insufficient information to invoke the tool correctly in a complex scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'intent, keyword, or tag,' which loosely maps to query and tags, but does not explicitly explain how the two parameters interact, whether they can be combined, or what format values should take. The mapping is too vague to reliably guide parameter usage.
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 action ('Search'), the resource ('all life science sources'), and the search modes ('by intent, keyword, or tag'). It distinguishes the tool from sibling tools like getToolInfo and callTool by framing it as a cross-source search operation.
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 the tool is for searching across life science sources, but it does not explicitly state when to use it versus alternatives or provide any exclusions. Sibling tools are generic, so the intended context is somewhat inferable but not directly 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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