spring-nacos-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct resource and action: diff config, get config (raw or app-level), list configs, list environments, list instances, list services, search config. No two tools have overlapping purposes, making selection unambiguous.
Naming Consistency5/5All tool names follow the consistent pattern 'nacos_verb_noun' in snake_case (e.g., nacos_diff_config, nacos_list_services). Verbs and nouns are clear and uniform, with no mixing of conventions.
Tool Count5/5With 8 tools covering both configuration and service discovery, the count is well-scoped for the domain. Each tool serves a distinct purpose without bloat or insufficiency.
Completeness4/5The toolset provides comprehensive read and comparison capabilities for Nacos configs and services, including diff, search, and app-level config resolution. It lacks write operations (create/update/delete), but given the diagnostic focus, this is a minor gap.
Average 3.9/5 across 8 of 8 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
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This repository is licensed under Apache 2.0.
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?
No annotations provided, so description must disclose behavioral traits. It only states it lists services but doesn't explain pagination behavior, return format, authentication needs, or whether filtering is supported. Very minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no fluff, but it is overly terse given 4 parameters, no output schema, and many siblings. Improved structure would help.
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?
The tool has 4 parameters and no output schema, and description does not explain return format, pagination, or behavior with large datasets. Incomplete for practical use.
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?
Schema coverage is 50% (env and group have descriptions, page_no/page_size have defaults only). The description adds no additional meaning to parameters, such as explaining 'group' or pagination semantics.
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 lists service names from Nacos naming/discovery registry in one environment, using specific verb 'list' and resource. It distinguishes from sibling tools like nacos_list_configs and nacos_list_instances.
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 on when to use this tool versus alternatives like nacos_search_config or nacos_list_instances. No mention of prerequisites or exclusions.
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 full burden. It mentions 'no content by default' and optional fuzzy filtering, but does not disclose pagination behavior, response format (e.g., list of dataId strings or full objects), or whether ordering applies.
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, well-structured sentence with a parenthetical clarification. It is front-loaded with the primary action and contains no fluff.
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 6 parameters, no output schema, and no annotations, the description covers the main purpose but lacks details on parameters like group, pagination behavior, and the structure of the response (what fields each config datum includes).
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 low (33%). The description adds meaning for data_id (fuzzy keyword) and hints at include_content ('no content by default'), but fails to explain group, page_no, page_size, and include_content semantics beyond defaults.
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: listing config dataIds in a namespace, with optional fuzzy filtering by dataId. It distinguishes itself from siblings like nacos_get_config (which retrieves a specific config) and nacos_search_config (more advanced search).
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 listing configs but does not explicitly guide when to use this tool versus alternatives like nacos_search_config or nacos_get_config. No when-not-to-use or alternative references are provided.
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, so the description carries the full burden of behavioral disclosure. It only describes the output (structured diff) but does not mention whether the operation is read-only, any authentication needs, or other side effects. For a diff tool, this is a significant gap.
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: first defines the core action and output, second gives a concrete usage example. No wasted words, and the most critical information is front-loaded.
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 absence of an output schema, the description adequately explains the input (two environments and a dataId) and the output (keys only in A, only in B, and changed values). It provides a clear use case. Could be slightly more detailed about the return format, but sufficient for an AI 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 input schema covers 75% of parameters with descriptions (env_a, env_b, data_id have descriptions; group lacks one). The description does not add any extra parameter meaning beyond the schema. A baseline of 3 is appropriate since the schema does most of the work.
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 the tool compares a config between two environments and returns a structured key-level diff, using a specific question as an example. This clearly distinguishes it from sibling tools like nacos_get_config (single env) or nacos_list_configs.
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 frames the tool as 'the best tool for questions like is X consistent between dev and test?', which clearly indicates when to use it. However, it does not explicitly state when not to use it or mention alternatives among the listed siblings.
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 correctly implies a read-only operation by listing instance details. However, it does not disclose potential behaviors like pagination, limits, or error responses (e.g., what if service is missing). The description is honest but lacks depth.
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-loading the goal and intended use. Every word contributes; no fluff or repetition.
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 and absence of an output schema, the description covers the main points: what is returned (IP, port, health) and when to use it. It lacks mention of pagination or ordering, but for a basic list tool, this is adequate.
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% for three parameters, so baseline is 3. The description adds no additional meaning beyond what the schema already provides (e.g., it doesn't explain that 'service_name' must match exactly, or discuss default groups). No value added.
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 it lists online instances with specific fields (IP, port, health) for a single service, and provides a concrete usage example ('is service X up / why is it offline'). This effectively distinguishes it from sibling tools like nacos_list_services (which lists services, not instances) and config-related 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 explicitly states when to use the tool: for service health/offline questions. It does not mention when not to use or alternative tools, but the context is clear enough given the sibling list and the specific instance focus.
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. The description implies a read-only operation by stating 'full-text search' but does not explicitly confirm safety or mention side effects, authentication needs, or rate limits. It adequately describes what it does but lacks explicit behavioral disclosure.
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-loading the main purpose and then a clear use case. Every sentence adds value, with no redundancy or unnecessary detail.
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 3 parameters (2 required) and no output schema, the description explains the return format and use case. It could clarify search limits or pagination, and the 'group' parameter remains unexplained. Overall, it provides enough context for basic usage.
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 67% (2 of 3 parameters described). The description adds meaning by explaining the search is over full content and returns matching dataIds and lines, but does not explain the 'group' parameter. It adds some value but does not fully compensate for the undocumented parameter.
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 it performs full-text search across config contents in one environment, returns matching dataIds and lines, and provides a specific use case (find which config file defines a property key). This distinguishes it from siblings like nacos_get_config and nacos_list_configs.
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 to find which config file defines a property key', providing clear context for when to use it. However, it does not mention when not to use it or name alternative tools, leaving some ambiguity.
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 full burden. It states it reads raw content but does not disclose potential errors if config not found, output format, or any side effects. For a simple read operation, it is adequate but lacks depth.
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 redundancy. First sentence states purpose, second provides usage guidance. Extremely 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?
Given the tool's simplicity, no output schema, and all parameters described in schema, the description is largely complete. It mentions 'raw content' but does not specify output format or error behavior. A minor gap, but overall adequate 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 coverage is 100% and the description does not add new parameter semantics beyond what the schema provides. The example dataId reinforces but does not extend schema meaning.
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 'Read', the resource 'raw content of one Nacos config', and specifies the method 'by its exact dataId'. It also gives an example. It distinguishes itself from nacos_search_config.
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 provides when to use this tool versus an alternative: 'Use nacos_search_config first when you don't know which dataId contains a key.' This is clear and helpful.
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 explains that the result includes own config plus shared configs, but does not disclose other behavioral traits like error handling, authorization needs, or rate limits. The read nature is implied but not explicitly stated.
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, every word serves a purpose. First sentence defines the tool, second gives a preference recommendation. No redundancy or unnecessary information.
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 no output schema, the description does not explain the return format or structure. It covers the config composition well but omits details about error cases, the role of the group parameter, and the exact interpretation of 'effective configuration'. The sibling list provides context but the description itself is not fully complete.
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 67% (group parameter lacks description). The description adds meaning by linking 'app' to the file extension pattern (<app>.<file-extension>) and mentions 'env' implicitly via shared configs. This compensates partly for the missing group description, but group remains unexplained.
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 clearly states it reads the effective configuration of an app, including its own config and shared/extension configs. It distinguishes itself from sibling nacos_get_config by specifying preference. This meets the highest standard for purpose clarity.
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 recommends preferring this tool over nacos_get_config when asked about an app's settings. This provides clear guidance for tool selection, leaving no ambiguity about when to use it.
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?
With no annotations, the description carries full burden. It explains the tool auto-discovers environments from application/bootstrap files, which is key behavioral info. It does not cover non-destructiveness or permissions, but for a read-only list these are implied.
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 purpose, no filler. Every sentence earns its place.
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?
Given zero parameters, no output schema, and 7 sibling tools, the description fully covers what the agent needs to know: what it lists and when to call it first.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, schema coverage 100% (empty). Description adds value by explaining what the output includes and the source of discovery, which is beyond the schema's empty definition.
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 'List' and resource 'environments (Spring profiles)', and specifies the returned details: server address, namespace, groups. It implicitly distinguishes from sibling tools which deal with configs, instances, and services.
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?
Explicitly advises to call this first if unsure which environments exist, providing clear usage context. Does not explicitly mention when not to use or alternatives, but the guidance is sufficient for the tool's simplicity.
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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