agentic-mcp-server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct operation: search returns matches, get retrieves a full document by slug, add creates a new document, and sys.time provides system time. There is no overlap in purpose or return type.
Naming Consistency5/5The knowledge base tools follow a consistent kb.<verb> pattern (search, get, add), and the system tool uses sys.time. Prefix-based namespaces make the convention predictable and easy to reason about.
Tool Count4/5Four tools is a compact but reasonable set for a focused knowledge base server with a system utility. It is not overly thin, though a couple more operations could strengthen the scope.
Completeness3/5The surface covers search, retrieval, and creation of knowledge base documents, but lacks update, delete, and list-all operations. This leaves notable CRUD gaps that agents cannot work around directly.
Average 4.3/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- 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.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the description does not need to repeat those. It adds no extra behavioral details beyond what the annotations provide, but it also does not contradict them.
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 compact and well-structured: one sentence states the core purpose and another covers the output and usage workflow. No unnecessary words or redundant details are present.
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?
Since there is no output schema, the description usefully specifies the return fields: slug, title, score, and snippet. It also explains the relationship with kb.get. It does not mention error cases or empty results, but for a search tool this is reasonably complete.
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 covers all parameters with descriptions: query, limit, and filter with nested tag and sort. The tool description adds no additional parameter-level detail beyond the schema, so it remains at the baseline for full schema 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 uses the specific verb 'search' and clearly identifies the resource as the markdown knowledge base. It states the tool returns best-matching documents, and the phrase 'Use this first when you need information you do not already have' clearly differentiates it from other retrieval tools like kb.get.
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 says to use this tool first when needing information, and it mentions using the returned slug with kb.get, which provides workflow context. It does not explicitly enumerate when not to use it or compare with kb.add or sys.time, but the guidance is clear enough.
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?
The annotations already declare readOnlyHint and idempotentHint as true, covering side-effect safety. The description adds the return format ('full markdown body') and that it returns a single document, but these are minor additions beyond the annotations.
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, focused sentence with no superfluous words. It is well-structured, front-loading the core action and then the parameter detail, making it easy to parse quickly.
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?
For a simple read-only tool with one parameter and no output schema, the description provides all necessary context: what it returns (full markdown body), how to identify the document (by slug), and where the slug comes from (kb.search). No critical information is missing.
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 schema provides a clear description for the slug parameter (including an example). The tool description reinforces this and adds the important context that the slug comes from kb.search, which helps the agent understand how to populate the parameter correctly.
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 action ('Return'), the resource ('knowledge-base document'), and the means ('by slug'). It also references kb.search for obtaining the slug, making the purpose unambiguous and distinct from the sibling tools.
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 implicitly guides usage by stating the slug is 'as returned by kb.search', which tells the agent to use kb.search first. However, it does not explicitly contrast with kb.add or state when not to use this tool, so it falls short of fully explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the output format (ISO 8601) and the optional timezone behavior, which goes beyond the readOnlyHint annotation. While the read-only nature is already declared, the description adds useful behavioral details about the response, such as format and timezone handling.
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, concise sentence that conveys all essential information without unnecessary wording. It is well-structured and directly states the tool's purpose and optional parameter.
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?
For a simple tool that returns the current time, the description, combined with the schema, covers all necessary context: what the tool does, the output format, and the parameter's meaning and default. No additional information is needed for a user to invoke it correctly.
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 already provides a clear description for the timeZone parameter, including an example and default behavior. The tool description adds no new information about the parameter beyond what is already in the schema, so it does not enhance the parameter semantics beyond the baseline.
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 function: returning the current date and time in ISO 8601 format, with an optional timezone parameter. It is specific about the resource (current time) and the action (return), leaving no ambiguity about what the tool does.
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 implicitly distinguishes this tool from the sibling knowledge-base tools (kb.search, kb.get, kb.add) by focusing on time retrieval. However, it does not explicitly state when to prefer this over alternatives, though the distinct purpose makes the use case obvious. A minor lack of explicit guidance prevents a perfect score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the write nature (matching readOnlyHint=false) and adds specific failure modes, going beyond the annotations to explain 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 concise, using two sentences that cover purpose and key constraints without unnecessary details.
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?
For a simple create operation, the description covers necessary context: what it does, when it fails, and the need for user confirmation. No output schema is required for this tool.
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 covers 'body' and 'slug' descriptions, but 'title' and 'tags' lack descriptions. The description text adds no parameter-specific information, so it does not compensate for the missing schema 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 action ('Create a new markdown document') and the resource ('knowledge base'), distinguishing it from sibling tools like kb.search and kb.get.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states failure conditions (writes disabled, slug already exists) and instructs the user to ask before calling, providing clear guidance on when to use the tool.
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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