Which integrations are available for this server?

Provides tools for managing and inspecting Nacos configurations and service discovery across Spring Cloud environments, enabling AI agents to list, get, search, and diff configs, as well as list services and instances.

spring-nacos-mcp

by kestiny18

Overview Schema Related Servers Score Discussions

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spring-nacos-mcp

中文文档

A project-aware, read-only Nacos MCP server for Spring Cloud repositories.

Point it at your Spring Cloud repo. It reads your own application-* / bootstrap-* files, discovers every environment (dev / test / pre / prod / ...), and gives your AI assistant read-only Nacos tools across all of them — no host, port, namespace or token to configure.

You:    "Is sso.server.productCode consistent between dev and test?"

Claude: → nacos_search_config(env=dev, keyword=sso.server.productCode)
        → nacos_diff_config(env_a=dev, env_b=test, data_id=sso.properties)

        "Yes — the value is identical in both environments (`PC-1001`).
         One related key differs though: sso.server.url points to
         dev-sso.corp.com in dev and test-sso.corp.com in test."

Why not the official `nacos-mcp-server`?

The official nacos-group/nacos-mcp-server connects to one cluster that you configure by hand (--host, --port, --access_token). That's the right tool for operating a Nacos cluster.

This project answers a different question: "what does my project's config look like across environments?"

	official nacos-mcp-server	spring-nacos-mcp
Setup	manual host/port/token per cluster	zero-config: parsed from your repo
Environments	one per server instance	all profiles, `env` param on every tool
Cross-env diff	not possible (single cluster)	built-in `nacos_diff_config`
Spring awareness	none	shared-configs, file-extension, app config
Write operations	planned	never (read-only by design)

Related MCP server: jewei-mcp-nacos

Quickstart

The easy way: let your AI agent install it

Paste this into Cursor / Claude Code / Codex / Trae:

Install the MCP server from https://github.com/kestiny18/spring-nacos-mcp into this project and verify it works.

The repo ships an llms-install.md with exact steps per client, so the agent can do the whole thing — download, config, verification — by itself.

Manual, option A: copy one file (no PyPI, no dependencies)

The whole server is a single, zero-dependency, standard-library-only Python file. Drop it into your repo:

curl -sfL -o tools/nacos_mcp.py https://raw.githubusercontent.com/kestiny18/spring-nacos-mcp/main/src/spring_nacos_mcp/server.py

// .cursor/mcp.json or .mcp.json (Claude Code), at the repo root
{
  "mcpServers": {
    "spring-nacos-mcp": { "command": "python", "args": ["tools/nacos_mcp.py"] }
  }
}

Works on intranet machines too — copy the file over however you like.

Manual, option B: uv / pip straight from git

{
  "mcpServers": {
    "spring-nacos-mcp": {
      "command": "uvx",
      "args": ["--from", "git+https://github.com/kestiny18/spring-nacos-mcp", "spring-nacos-mcp"]
    }
  }
}

Or pip install git+https://github.com/kestiny18/spring-nacos-mcp and use the spring-nacos-mcp command.

The server auto-detects the repo root from its working directory (your editor's workspace). For clients that don't launch servers in the workspace (e.g. Claude Desktop), pin it: "args": [..., "--repo", "/path/to/repo"].

Verify your setup

python tools/nacos_mcp.py --check       # or: spring-nacos-mcp --check

Prints every discovered environment, where it came from, and whether the Nacos server is reachable. Exit codes: 0 all reachable · 1 nothing discovered · 2 discovered but some unreachable (usually VPN/network, not setup).

Tools

Tool	What it does
`nacos_list_envs`	List discovered environments with address/namespace/groups
`nacos_get_config`	Read one config's raw content by dataId
`nacos_get_app_config`	App config + the shared/extension configs your project declares
`nacos_list_configs`	List dataIds in a namespace (optional fuzzy filter)
`nacos_search_config`	Full-text search across all config contents
`nacos_diff_config`	Key-level diff of one config between two environments
`nacos_list_services`	List services in the discovery registry
`nacos_list_instances`	List online instances (IP/port/health) of a service

How discovery works

Find the repo root (.git, pom.xml, build.gradle, mvnw, gradlew, ...).
Scan every */src/main/resources/ for application[-<profile>].{yml,yaml,properties} and bootstrap[-<profile>].{yml,yaml,properties}. Multi-document YAML with spring.config.activate.on-profile (or legacy spring.profiles) is supported.
For each profile, merge sources in priority order: bootstrap-<profile> → application-<profile> → base bootstrap → base application.
Extract spring.cloud.nacos.*: server-addr, namespace, username/password, config group (also from spring.config.import: nacos:...?group=X), discovery group, file-extension, shared-configs / extension-configs / legacy shared-dataids. Relaxed binding (server-addr / serverAddr / server_addr) is handled.
${...} placeholders are resolved from environment variables (${nacos.addr} also tries NACOS_ADDR); ${name:default} uses the default. Environments with unresolved placeholders are skipped with a clear log line.

Overrides

Environment variables (highest precedence), <ENV> is the upper-cased profile name:

NACOS_DEV_SERVER_ADDR / NACOS_DEV_NAMESPACE / NACOS_DEV_USERNAME /
NACOS_DEV_PASSWORD / NACOS_DEV_GROUP / NACOS_DEV_CONTEXT_PATH
NACOS_USERNAME / NACOS_PASSWORD          # global fallback credentials

Or a .spring-nacos-mcp.yml at the repo root — patch discovered environments or define ones that aren't in the repo at all:

envs:
  staging:
    server-addr: nacos-staging.corp.com:8848
    namespace: ns-staging
    username: readonly
    password: ${STAGING_NACOS_PASSWORD}   # resolved from env var

Security notes

Read-only by construction: the only endpoints ever called are config/service GET queries and the login endpoint. There is no code path that writes to Nacos.
Config content reaches the LLM. If your configs contain secrets, enable masking: SPRING_NACOS_MCP_MASK=1 masks values whose keys contain password/secret/token/credential/..., or provide your own list: SPRING_NACOS_MCP_MASK=password,apikey. Masking is off by default.
Prefer a read-only Nacos account (via NACOS_USERNAME / NACOS_PASSWORD) over credentials committed in config files.

Compatibility

Python ≥ 3.9, zero runtime dependencies.
Nacos 1.x / 2.x via the v1 OpenAPI; auth via /v1/auth/login with automatic fallback to /v3/auth/user/login (Nacos 3.x). https:// server addresses and comma-separated cluster address lists are supported.
Nacos 3.x keeps v1 OpenAPI compatibility in current releases; if your deployment disables it, please open an issue — a v3 API backend is on the roadmap.

Limitations

The built-in YAML parser covers the subset used by Spring config files (nested maps, lists, multi-document). Anchors and flow collections are ignored.
Placeholders that come from Maven profile filtering (@...@) are not resolved; use the override file for those repos.

License

Apache-2.0

Available Tools

8 tools

nacos_diff_configA

Compare one config (dataId) between two environments and return a structured key-level diff: keys only in A, only in B, and changed values. The best tool for questions like 'is X consistent between dev and test?'.

ParametersJSON Schema

Name	Required	Description
`env_a`	Yes	First environment
`env_b`	Yes	Second environment
`data_id`	Yes	Exact dataId to compare
`group`	No

TDQS

A3.8/5.0

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.

Conciseness5/5

Is 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.

Completeness4/5

Given 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.

Parameters3/5

Does 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.

Purpose5/5

Does 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 Guidelines4/5

Does 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.

nacos_get_app_configA

Read the effective configuration of one application: its own config (.) plus the shared/extension configs declared in the project (spring.cloud.nacos.config.shared-configs). Prefer this over nacos_get_config when asked about an app's settings.

ParametersJSON Schema

Name	Required	Description
`env`	Yes	Target environment (Spring profile)
`app`	Yes	Application name (spring.application.name) or a full dataId
`group`	No

TDQS

A4.3/5.0

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.

Conciseness5/5

Is 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.

Completeness3/5

Given 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.

Parameters4/5

Does 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.

Purpose5/5

Does 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 Guidelines5/5

Does 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.

nacos_get_configA

Read the raw content of one Nacos config by its exact dataId (e.g. 'order-service.properties'). Use nacos_search_config first when you don't know which dataId contains a key.

ParametersJSON Schema

Name	Required	Description
`env`	Yes	Target environment (Spring profile)
`data_id`	Yes	Exact dataId, e.g. order-service.properties
`group`	No	Config group; defaults to the group from project config

TDQS

A4.2/5.0

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.

Conciseness5/5

Is 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.

Completeness4/5

Given 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.

Parameters3/5

Does 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.

Purpose5/5

Does 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 Guidelines5/5

Does 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.

nacos_list_configsA

List config dataIds in an environment's namespace (no content by default). Optionally fuzzy-filter by dataId substring.

ParametersJSON Schema

Name	Required	Description
`env`	Yes	Target environment (Spring profile)
`group`	No
`data_id`	No	Optional dataId fuzzy keyword
`page_no`	No
`page_size`	No
`include_content`	No

TDQS

A3.7/5.0

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.

Conciseness5/5

Is 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.

Completeness3/5

Given 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.

Parameters3/5

Does 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.

Purpose5/5

Does 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 Guidelines3/5

Does 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.

nacos_list_envsA

List the environments (Spring profiles) auto-discovered from this repository's application/bootstrap files, with each environment's Nacos server address, namespace and groups. Call this first if you are unsure which environments exist.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A4.6/5.0

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.

Conciseness5/5

Is 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.

Completeness5/5

Given 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.

Parameters5/5

Does 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.

Purpose5/5

Does 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 Guidelines4/5

Does 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.

nacos_list_instancesA

List the online instances (IP, port, health) of one service. Use for 'is service X up / why is it offline' questions.

ParametersJSON Schema

Name	Required	Description
`env`	Yes	Target environment (Spring profile)
`service_name`	Yes	Service name as registered in Nacos
`group`	No	Service group, default DEFAULT_GROUP

TDQS

A4/5.0

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.

Conciseness5/5

Is 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.

Completeness4/5

Given 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.

Parameters3/5

Does 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.

Purpose5/5

Does 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 Guidelines4/5

Does 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.

nacos_list_servicesC

List service names registered in the Nacos naming/discovery registry of one environment.

ParametersJSON Schema

Name	Required	Description
`env`	Yes	Target environment (Spring profile)
`group`	No	Service group, default DEFAULT_GROUP
`page_no`	No
`page_size`	No

TDQS

C2.9/5.0

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.

Conciseness3/5

Is 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.

Completeness2/5

Given 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.

Parameters2/5

Does 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.

Purpose5/5

Does 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 Guidelines2/5

Does 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.

nacos_search_configA

Full-text search across all config contents in one environment. Returns matching dataIds with the matching lines. Use this to find which config file defines a property key.

ParametersJSON Schema

Name	Required	Description
`env`	Yes	Target environment (Spring profile)
`keyword`	Yes	Case-insensitive keyword
`group`	No

TDQS

A4/5.0

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.

Conciseness5/5

Is 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.

Completeness4/5

Given 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.

Parameters3/5

Does 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.

Purpose5/5

Does 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 Guidelines4/5

Does 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.

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TDQS

A3.9/5.0

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 Consistency5/5

All 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 Count5/5

With 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.

Completeness4/5

The 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.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

GitHub Repository

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