Clixon MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: fetch_config retrieves configuration from a device, get_config accesses the cached configuration, and get_config_path extracts specific sections from the cache. There is no overlap or ambiguity in their functions.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with snake_case (fetch_config, get_config, get_config_path). The verbs 'fetch' and 'get' are semantically related but used distinctly to differentiate between external retrieval and internal access.
Tool Count3/5With only 3 tools, the set feels thin for a network device configuration server, potentially lacking operations like update, delete, or validation. However, it covers basic fetch and query workflows, making it borderline but functional for limited use cases.
Completeness2/5The toolset is severely incomplete for network device configuration management. It only supports fetching and reading configuration, with no tools for creating, updating, deleting, or validating configurations, leaving significant gaps that will hinder agent workflows.
Average 3.8/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions authentication (HTTP basic auth) and SSL verification, which adds useful context beyond the schema. However, it lacks details on rate limits, error handling, response format, or whether this is a read-only operation, leaving gaps for a tool that interacts with network devices.
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 well-structured with a brief purpose statement followed by a parameter list. It's appropriately sized and front-loaded, with no wasted sentences. Minor improvements could include bolding or bullet points for better readability, but it's efficient overall.
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?
Given the tool's complexity (network device interaction) and the presence of an output schema (which handles return values), the description is moderately complete. It covers parameters well but lacks behavioral context like error handling or performance considerations. With no annotations, it should do more to guide safe and effective use.
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 description coverage is 0%, so the description must compensate. It provides clear explanations for all 4 parameters (url, username, password, verify_ssl), including examples and defaults, adding significant meaning beyond the bare schema. This effectively documents the parameters, though it could benefit from more detail on URL format or authentication requirements.
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 action ('fetch') and target ('network device configuration via RESTCONF'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its siblings (get_config, get_config_path), leaving ambiguity about when to use one versus the others.
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 provided on when to use this tool versus the sibling tools (get_config, get_config_path). The description mentions the protocol (RESTCONF) but doesn't specify use cases, prerequisites, or alternatives, offering minimal contextual direction.
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 full burden. It discloses that the tool returns cached data and requires a prior fetch_config call, adding useful behavioral context. However, it doesn't cover aspects like error handling, performance, or what happens if cache is empty, 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, front-loaded with the main purpose and followed by a prerequisite note. Every sentence adds value without waste, making it highly efficient 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?
Given the tool has 0 parameters, an output schema exists, and no annotations, the description is mostly complete. It explains the purpose and prerequisite, but could benefit from more detail on cache behavior or output format, though the output schema mitigates this gap.
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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for this case is 4, as it avoids redundancy while being complete for a parameterless tool.
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 action ('Return') and resource ('currently cached RESTCONF configuration'), providing a specific purpose. However, it doesn't explicitly differentiate from sibling tools like 'get_config_path' beyond mentioning 'fetch_config' as a prerequisite.
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 by stating 'Call fetch_config first to load configuration from a device,' which guides when to use this tool. It implies an alternative (fetch_config) but doesn't explicitly mention when not to use it or compare with other siblings like get_config_path.
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. It discloses that the tool extracts from 'cached configuration', which implies read-only behavior, but doesn't mention error handling, performance, or what happens if the path doesn't exist. It adds some behavioral context but lacks completeness.
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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a clear 'Args' section with examples. Every sentence earns its place with no wasted words.
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 moderate complexity (1 parameter, no annotations, but with output schema), the description is mostly complete. It explains the purpose and parameter semantics well, but since there's an output schema, it doesn't need to describe return values. However, it could better address behavioral aspects like error cases.
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 input schema has 0% description coverage, so the description must compensate. It adds significant meaning by explaining the 'path' parameter as a 'dot-separated path into the config' with concrete examples, which clarifies the parameter's purpose and format beyond the schema's basic type.
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 with specific verb ('Extract') and resource ('specific section from the cached configuration'), and distinguishes it from siblings by specifying the dot-separated path mechanism. It's not just a tautology of the name.
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 for when to use this tool (extracting sections by dot-separated path), but doesn't explicitly mention when not to use it or name alternatives like 'fetch_config' or 'get_config'. It implies usage through the example paths.
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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