stack-overflow-mcp-light
Server Quality Checklist
Latest release: v1.2.0
- Disambiguation3/5
search_questions and search_questions_by_tag overlap because search_questions accepts advanced filters that likely include tag filtering, making the distinction unclear. fetch_question_answers is clearly distinct, retrieving a specific question with answers, but the two search tools create ambiguity.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern: search_questions, search_questions_by_tag, and fetch_question_answers. The 'by_tag' modifier is a clear exception for the second search tool but still follows the same convention, making the naming predictable and uniform.
Tool Count4/5With 3 tools, the set is on the lean side but appropriate for a 'light' Stack Overflow read-only server. Each tool serves a core purpose without redundancy, and the count is reasonable for the intended narrow scope.
Completeness4/5The server covers essential read operations: searching questions generically and by tag, and fetching a question with answers. Missing operations like user lookups or comment retrieval are not critical for a lightweight server, but the surface is slightly thin for full Stack Overflow coverage.
Average 3.4/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on
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- 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
- 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 disclosing behavioral traits. It only states that the tool searches and returns a list, offering no information about read-only safety, authentication requirements, pagination behavior, or any side effects. This is insufficient for an agent to safely invoke the 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 highly concise, using only three short sections (summary, Args, Returns) with no extraneous words. The structure is clean and front-loaded with the main purpose, making it easy to parse.
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 the complexity of a nested request object with many filters, the description is too thin. It fails to explain when to use this tool versus siblings, does not mention important behaviors like pagination limits or read-only status, and offers no guidance on constructing the request. The output schema may exist, but the description itself leaves significant gaps for an agent.
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 description adds a minimal summary of the 'request' parameter as containing filters and pagination, but since the schema description coverage is 0% for the top-level parameter, it does not fully compensate. The nested schema properties are richly described, so the agent can infer structure, but the description adds little beyond the obvious.
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 searches Stack Overflow questions using advanced filters, which specifies both the verb and resource. However, it does not explicitly differentiate from sibling tools like search_questions_by_tag, so it is clear but not fully distinguishing.
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 such as search_questions_by_tag or fetch_question_answers. It does not mention any exclusions or context for choosing this tool over others, leaving the agent to infer usage from the name alone.
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 transparency burden. It discloses that answers are sorted and include body content, but does not mention pagination, rate limits, authentication, or potential errors. For a read-only fetch tool, this is moderate but not comprehensive.
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 concise and structured with Args/Returns sections. It contains no fluff, though it could be slightly more efficient. It earns a high score for clarity and brevity.
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?
The description explains the tool's return value (question with sorted answers and body content), which is sufficient given the presence of an output schema. It does not mention edge cases or limitations, but for a simple fetch tool it covers the essential context.
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?
The description only vaguely mentions 'request' with ID and answer sorting options, adding little beyond the input schema which already provides detailed descriptions for question_id, sort, order, and page_size. With 0% schema description coverage, the description should compensate but does not.
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 fetches a specific Stack Overflow question with its answers, using a specific verb and resource. This distinguishes it from sibling search tools, which focus on finding questions rather than retrieving a particular question.
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 have a specific question ID and want answers, but does not explicitly mention the search siblings or state when not to use this tool. No exclusions or alternatives are provided, so guidance is only implicit.
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 carries the full burden. It states that it returns a list of question items, which is useful. However, it does not disclose any potential side effects (though as a search it is read-only), authentication requirements, rate limits, or error behaviors. The description is minimally transparent but not rich in behavioral detail.
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 concise, using a clear format with Args and Returns sections. It is easy to scan and not overly verbose. Minor redundancy exists between 'specific tag' and 'with the specified tag', but it does not detract significantly from clarity.
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 is relatively simple, and the output schema likely covers return values. The description does not mention pagination specifics or any edge cases, but the schema provides details. Without annotations, some additional context (e.g., rate limits, typical usage) would improve completeness, but it is adequate for a straightforward search 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?
The description summarizes the single parameter as 'Request with tag name, sort options, and pagination', which provides a high-level overview. Although schema description coverage is low (0%), the schema itself contains detailed descriptions for each field, so the agent can access those. The description adds some semantic framing but does not elaborate on specific fields like order or page_size.
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 explicitly states 'Search Stack Overflow questions that have a specific tag', which clearly defines the action (search), the resource (Stack Overflow questions), and the distinguishing qualifier (specific tag). This differentiates it from sibling tools like search_questions (general search) and fetch_question_answers (fetching answers).
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 clearly implies the use case: find questions for a specific tag. It does not explicitly mention alternatives or exclusions, but the tag-specific focus is evident from the first line. This provides clear context without stating when not to use it.
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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