blocket-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: general search, car search, boat search, motorcycle search, ad details, and filter options. Even the three vehicle searches are distinguishable by vehicle type and specialized filters.
Naming Consistency5/5All tool names follow a consistent lowercase underscore pattern with verbs like list, search, and get. The specialized searches (search_cars, search_boats, search_motorcycles) fit the same pattern as the base search.
Tool Count5/5Six tools is well-scoped for a marketplace search server. It covers general listings, vehicle-specific filters, ad details, and filter enums without unnecessary bloat.
Completeness5/5The surface covers the core read-only workflow: discover filter options, search across categories, and fetch full ad details. No obvious gaps for the stated domain.
Average 3.9/5 across 6 of 6 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 status not available
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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?
No annotations are provided, so the description must carry the burden. It discloses the return format ('Returns JSON with a docs array') and a key filtering pitfall (locations are counties, not cities). It does not mention pagination, rate limits, or explicitly state read-only behavior, but 'search' implies a safe read operation.
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?
Two sentences, no fluff. First sentence states purpose, second covers output format and a caveat. Every word earns its place; front-loaded 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?
The schema is rich, but there is no output schema, so the description should explain return values better than just 'docs array of matching ads'. It misses details about ad fields, pagination, and does not mention the relationship to list_filter_options for sub-category values. Adequate but 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?
The input schema provides 100% description coverage for all 6 parameters, including enums and examples. The description adds only a single clarification about the locations parameter (county vs city), which is minor. Baseline 3 is appropriate since 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?
Description states 'Search Blocket for general listings' with explicit examples (electronics, furniture, clothing). This clearly differentiates it from sibling tools like search_cars, search_boats, and search_motorcycles. The verb 'Search' names the action and resource.
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 general-listing usage via 'general listings' and examples, contrasting with vehicle-specific siblings. However, it does not explicitly name alternatives or state when not to use this tool. The location clarification ('län, not city') provides a useful usage hint but not tool-selection guidance.
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 present, so the description carries the burden of behavioral disclosure. It adds a useful spelling note about 'milage', but this is already in the schema. It does not explicitly confirm read-only behavior or describe return format, though 'Search' implies a safe query. Adequate but not rich.
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 exactly two sentences, front-loaded with the core purpose and followed by a brief, relevant spelling caveat. There is no wasted text or unnecessary detail, making it highly concise and scannable.
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 schema handles parameter details comprehensively, but there is no output schema and the description does not mention the return structure or pagination behavior. Given the tool's search nature, the description leaves some ambiguity about what the agent will receive, making it minimally complete but not fully self-sufficient.
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 provides 100% description coverage for all 17 parameters, so the baseline is 3. The description only summarizes filter groups (make, year, mileage, etc.) and repeats the milage spelling note, adding minimal semantic value beyond what the schema already communicates.
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 used cars on Blocket, a specific resource and platform, and lists the key filter dimensions (make, year, mileage, transmission, color, horsepower). This immediately distinguishes it from sibling tools like search_boats and search_motorcycles, making the purpose unambiguous.
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 use for car-specific searches with vehicle filters, but it does not explicitly contrast with generic 'search' or the boat/motorcycle variants, nor does it state when not to use it. The reference to vehicle-specific filters provides indirect context, but no direct guidance on alternatives.
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 the burden of behavioral disclosure. 'Search' implies a read-only operation, but no additional traits (e.g., pagination behavior, rate limits, or that it returns a list of ads) are disclosed. It is minimally transparent but not misleading.
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, information-dense sentence (11 words) that front-loads the tool's core purpose and differentiator. Every word earns its place, with no redundancy or filler.
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 complexity (10 parameters) and no output schema, the description is somewhat minimal but adequate. It correctly identifies the domain (Blocket boats) and key filter groups. However, it omits mention of other important filter dimensions (e.g., location, sort order) and the return type, though the rich schema partially compensates.
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%, with every parameter described. The description mentions 'type, length, price' as boat-specific filters, which maps to schema parameters but adds no new syntax or format details. With full schema coverage, a baseline of 3 is appropriate.
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 verb ('Search'), resource ('used boats on Blocket'), and scope ('boat-specific filters'), directly distinguishing it from sibling tools like search_cars and search_motorcycles. It is specific and unambiguous, leaving no doubt 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 Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by mentioning 'used boats on Blocket,' but it does not explicitly state when to prefer this over sibling tools like 'search' or 'search_cars.' No exclusions or alternative recommendations are provided, so guidance is only implied.
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 transparency burden. It discloses that the tool searches used (not new) motorcycles and mentions filter categories, but does not describe return format, pagination, or any side effects. As a search tool, the behavior is inherently safe, but the description adds limited behavioral context beyond what the schema already provides.
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 gets straight to the point with no filler. It earns a 5 for concise structure.
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 11 parameters and no output schema or annotations. The description covers the core purpose and a few representative filters but omits mention of location filtering, sort order, pagination, and the full range of makes/types. It is adequate but not fully comprehensive given the tool's complexity.
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%, and the description lists a subset of filter types (make, type, engine volume, price) that aligns with the schema. Since the schema already documents all 11 parameters, the description adds no additional parameter semantics, meriting the baseline score of 3.
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 specifies the verb 'Search' and the resource 'used motorcycles on Blocket', and distinguishes itself from sibling tools like search_cars and search_boats by focusing on motorcycles with MC-specific filters.
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: it is for searching used motorcycles on Blocket. It does not explicitly list exclusions or alternatives, but the tool's name and description make its applicable use case obvious. It could benefit from stating 'use this for motorcycle queries', but the context is clear.
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 must carry the burden of behavioral disclosure. It states the lists are 'static,' implying a read-only, predictable operation, which is helpful. However, it does not mention response format, caching, or any potential error behavior, leaving some gaps.
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 two sentences long, front-loaded with the core action, and every word adds value. It efficiently conveys what the tool does and when to use it without redundancy.
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 optional parameter, no output schema), the description is sufficiently complete. It tells the agent what the tool returns and when to use it, and the sibling tools provide enough context to avoid confusion. A slightly richer note on response shape or filtering behavior would push it to 5.
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 input schema already provides a complete enum of valid groups with a description for each parameter, achieving 100% schema coverage. The description adds a few examples that overlap with the schema but does not introduce meaningful new semantics, so the baseline 3 is appropriate.
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 ('Return') and clearly identifies the resource ('static enum lists for BlocketAPI filters'), with concrete examples (locations, categories, car models, boat types). This distinguishes it from sibling search tools, which query ads rather than provide filter options.
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 'Use this when you need valid enum values without guessing,' providing clear context for when to invoke the tool. It does not mention when not to use it or name alternatives, but the sibling tools are search-oriented, making the intended use obvious.
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 transparency burden. It only says 'full details' without specifying what that includes, error behavior, or any side effects. It does not clarify whether this is a read-only operation or what happens if the ID is invalid.
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?
Two sentences, front-loaded with the core action, and no wasted words. Every sentence adds necessary context.
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 retrieval tool with 2 fully documented params and no output schema, the description is adequate. It could be more explicit about the return value, but the phrase 'full details' covers the basic expectation.
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 100%, but the description adds valuable semantics by explaining how the 'type' enum corresponds to different search types (recommerce for general search, car/boat/mc for vehicle searches). This goes beyond the schema's enum list.
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 specific Blocket listing by ID and ad type.' It names a specific verb ('Get'), resource ('Blocket listing'), and scope ('by ID and ad type'), distinguishing it from sibling search tools.
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?
Provides explicit usage guidance: 'Use an id from search results. Match type to the search that found it (recommerce for general search, car/boat/mc for vehicle searches).' This tells the agent exactly how to select parameters and ties the tool to sibling search functions.
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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