Semantic Search MCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool serves a distinct purpose: semantic search, duplicate detection, and content retrieval. There is no overlap or ambiguity between them.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern (search_related, check_duplicates, get_content) using snake_case. The naming is predictable and readable.
Tool Count5/5Three tools is an appropriate, focused set for a semantic search server. Each tool earns its place and the scope is well-defined.
Completeness5/5The server covers the core needs of semantic search: finding related notes, detecting duplicates, and retrieving content. There are no missing operations that would hinder its stated purpose.
Average 3.6/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 27 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 passing
This repository is licensed under BSD 2-Clause "Simplified" License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 carries the full burden of behavioral disclosure. It only states the primary action but does not disclose edge cases (e.g., file not found, path resolution), or behavior around optional parameters like snippet and query despite their existence in the schema. This leaves significant behavioral aspects undisclosed.
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, tightly worded sentence that immediately conveys the core purpose. There is no fluff or redundancy, and the information is front-loaded. For the tool's purpose, this length is appropriately concise.
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?
The tool has moderate complexity with optional snippet/query parameters and an output schema, and the schema covers parameter semantics. However, the description is thin on operational context, such as how path resolution works or when to use snippet mode. While not incomplete for basic selection, the description itself needed to provide more contextual glue; the schema partially compensates, but gaps remain.
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 a baseline of 3 is appropriate. The description itself does not add any parameter semantics beyond the schema, but the schema already documents each parameter (path, query, snippet, context_lines) clearly. The description neither enhances nor detracts from what the schema provides.
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 ('Fetch the content of a file') and the resource ('indexed vault'), using a specific verb and resource. It distinguishes itself from sibling tools 'search_related' and 'check_duplicates' by focusing on direct content retrieval rather than search or duplication checks.
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 related tools or any exclusionary conditions (e.g., 'use search_related instead when looking for related content'). The intended usage is only implicitly derived from the tool's name and action.
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, and the description does not disclose behavioral details beyond the basic 'Find' action—such as how duplicates are determined, whether the operation is read-only, or any side effects. The burden falls on the description, which is minimal.
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 with no wasted words, making it highly concise 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 (one parameter, output schema present), the description conveys the main purpose adequately. However, it lacks guidance on when to use vs alternatives, which is somewhat a gap but not critical for such a straightforward 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 description coverage is 100% for the single parameter, so the schema fully describes file_path. The description adds no extra semantic meaning beyond what the schema already states.
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 a specific verb ('Find') and resource ('notes that are potential duplicates of the given file'), clearly distinguishing it from sibling tools like search_related and get_content.
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 for checking duplicates but does not explicitly state when to use this tool versus alternatives, nor any exclusions or prerequisites.
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 adds the key trait that the search is semantic (not lexical), but it does not explicitly state whether the operation is read-only or if there are any side effects. The word 'search' implies safety, but this is not confirmed.
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, clear sentence with no redundant words. It is front-loaded with the action and directly conveys the core functionality, 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.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with full schema coverage and an output schema present, the description is largely complete. It explains the main purpose and semantically relevant behavior. However, it lacks explicit usage guidance and does not confirm the read-only nature in the absence of annotations, leaving minor 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 coverage is 100%: both 'query' and 'top_k' have descriptions in the input schema. The description does not add any additional parameter semantics beyond what is already in the schema, so the baseline score of 3 applies.
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 searches for notes semantically related to the query text. It specifies a concrete action (search), the resource (notes), and the nature (semantic relatedness), which effectively distinguishes it from sibling tools like check_duplicates and get_content.
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 you need semantically related notes) but does not explicitly mention alternatives or exclusions. No guidance is given on when to choose this tool over check_duplicates or get_content, though the semantic focus provides some context.
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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- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
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