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promptz.dev MCP Server

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promptz.dev MCP 服务器

在 Amazon Q Developer 中直接访问来自 promptz.dev 的提示。

此 MCP 服务器允许从 promptz.dev API 访问提示而无需复制粘贴，从而减少开发工作流程中的上下文切换和摩擦。

特征

promptz.dev MCP 服务器提供两项主要功能：

  1. 提示——可执行函数来搜索和执行提示。

  2. 规则- 可执行函数用于搜索项目规则并通过与其他工具集成在您的工作区中添加/更新它们。

Related MCP server: prompts.chat MCP Server

示例用法

一旦服务器连接到 Amazon Q Developer，您就可以使用自然语言，例如：

  • “搜索有关 JavaScript 的 CLI 提示”

  • “向我显示名为‘React 组件文档’的提示”

  • “使用 React 组件文档提示来改进我的文档”

  • “查找 CDK 开发的项目规则”

  • “将 CDK 项目结构项目规则添加到我的工作区”

安装

步骤 1：获取 API 凭证

  1. 导航至https://promptz.dev/mcp

  2. 复制 MCP 设置，如 API 密钥、API URL 或示例 MCP 配置片段。

步骤 2：安装 MCP 服务器

打开位于~/.aws/amazonq/mcp.json的 Amazon Q Developer MCP 客户端设置文件

选项 1：使用 npx（推荐）

使用服务器的最简单方法是使用 npx，它不需要安装：

  1. 将以下配置添加到您的 Amazon Q Developer MCP 客户端的设置文件中：

{
  "mcpServers": {
    "promptz.dev": {
      "command": "npx",
      "args": ["-y", "@promptz/mcp"],
      "env": {
        "PROMPTZ_API_URL": "your-api-url-from-promptz.dev",
        "PROMPTZ_API_KEY": "your-api-key-from-promptz.dev"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

选项 2：本地安装

  1. 克隆存储库：

git clone https://github.com/cremich/promptz-mcp.git
cd promptz-mcp

  1. 安装依赖项并构建：

npm install
npm run build

  1. 将以下配置添加到您的 MCP 客户端的设置文件：

{
  "mcpServers": {
    "promptz.dev": {
      "command": "node",
      "args": ["/path/to/promptz-mcp/build/index.js"],
      "env": {
        "PROMPTZ_API_URL": "your-api-url-from-promptz.dev",
        "PROMPTZ_API_KEY": "your-api-key-from-promptz.dev"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

故障排除

如果您遇到服务器问题：

  1. 检查您的 API 凭证是否正确

  2. 确保服务器在 MCP 客户端中正确配置

  3. 在位于~/.promptz/logs/mcp-server.log日志中查找错误消息

  4. 使用 MCP Inspector 进行调试：

# Run with environment variables
PROMPTZ_API_URL="your-api-url" PROMPTZ_API_KEY="your-api-key" npm run inspector

检查器将提供一个 URL 来访问浏览器中的调试工具。

发展

对于那些想要贡献或修改服务器的人：

# Install dependencies
npm install

# Build the server
npm run build

# For development with auto-rebuild
npm run watch

# Run tests
npm test

安全注意事项

  • 该服务器仅提供对提示的读取权限，不执行任何写入操作

  • API 凭证存储在您的 MCP 客户端的配置文件中

  • 与 promptz.dev API 的所有通信均通过 HTTPS 完成

  • 服务器记录到您的主目录中的文件（~/.promptz/logs/mcp-server.log）

Available Tools

4 tools
get_promptC

Get a specific prompt by ID or name

ParametersJSON Schema
NameRequiredDescriptionDefault
nameNoName of the prompt to retrieve

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool retrieves a prompt but doesn't describe what happens if the prompt doesn't exist (e.g., error handling), authentication needs, rate limits, or the format of the returned prompt. For a retrieval tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, achieving optimal conciseness for the tool's purpose.

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?

Given the tool's simplicity (1 parameter, 100% schema coverage) but lack of annotations and output schema, the description is incomplete. It doesn't explain the return value (e.g., prompt content or metadata), error conditions, or behavioral nuances. For a retrieval tool, this leaves the agent without key operational context.

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 description coverage is 100%, with the single parameter 'name' documented as 'Name of the prompt to retrieve'. The description adds that retrieval can be by 'ID or name', implying an alternative identifier not in the schema, but doesn't clarify how to specify an ID versus a name or if both are supported. This adds marginal value beyond the schema, meeting the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('a specific prompt'), specifying retrieval by ID or name. It distinguishes from 'list_prompts' (which likely lists multiple prompts) but doesn't explicitly differentiate from 'get_rule' or 'list_rules', which operate on different resource types. The purpose is clear but sibling differentiation is incomplete.

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 is provided on when to use this tool versus alternatives. The description doesn't mention when to choose 'get_prompt' over 'list_prompts' (e.g., for detailed vs. summary views) or how it relates to 'get_rule' and 'list_rules'. Usage context is implied by the name but not explicitly stated, leaving gaps for the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_ruleC

Get a specific project rule by name

ParametersJSON Schema
NameRequiredDescriptionDefault
nameNoName of the rule to retrieve

TDQS

C2.9/5.0
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 behavioral disclosure. It states the action ('Get') but doesn't describe whether this is a read-only operation, what happens if the rule doesn't exist, permissions required, or response format. This leaves significant gaps for a tool with no annotation coverage.

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, efficient sentence with no wasted words, clearly front-loading the core action. It's appropriately sized for a simple tool with one parameter.

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?

Given no annotations, no output schema, and a simple input schema, the description is incomplete. It lacks information on behavioral aspects like error handling, return values, or usage context, which are crucial for effective tool invocation by 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?

Schema description coverage is 100%, with the single parameter 'name' documented in the schema as 'Name of the rule to retrieve'. The description adds no additional parameter details beyond this, so it meets the baseline for high schema coverage without compensating value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('a specific project rule by name'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_rules' (which likely lists multiple rules vs. retrieving one specific rule).

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 is provided on when to use this tool versus alternatives like 'list_rules' or other siblings. The description implies usage for retrieving a specific rule by name but doesn't clarify prerequisites, error conditions, or comparative contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_promptsC

List available prompts from promptz.dev

ParametersJSON Schema
NameRequiredDescriptionDefault
cursorNoPagination token for fetching the next set of results
tagsNoFilter prompts by tags (e.g. ['CLI', 'JavaScript'])

TDQS

C2.9/5.0
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 behavioral disclosure but only states the basic action. It doesn't mention whether this is a read-only operation, how results are returned (e.g., pagination behavior implied by the 'cursor' parameter), rate limits, authentication needs, or what 'available prompts' means in context. This leaves significant gaps for a listing tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information, making it easy to parse quickly.

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?

Given no annotations and no output schema, the description is incomplete for a tool with two parameters and implied pagination behavior. It doesn't explain what 'available prompts' includes (e.g., public vs. private), how results are structured, or error conditions, leaving the agent with insufficient context for reliable use.

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 description coverage is 100%, with both parameters ('cursor' and 'tags') clearly documented in the schema. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline of 3 where the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and resource ('available prompts from promptz.dev'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'get_prompt' (which likely retrieves a single prompt) or 'list_rules' (which likely lists rules rather than prompts), missing the opportunity for full sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_prompt' or 'list_rules'. There's no mention of use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_rulesB

List available project rules from promptz.dev

ParametersJSON Schema
NameRequiredDescriptionDefault
cursorNoPagination token for fetching the next set of results
tagsNoFilter rules by tags (e.g. ['CDK', 'React'])

TDQS

B3.1/5.0
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 behavioral disclosure but only states what the tool does without mentioning safety, permissions, rate limits, or response format. It lacks details on whether this is a read-only operation, what happens on errors, or how results are structured.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 the tool's moderate complexity (list operation with filtering and pagination), no annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but lacks behavioral context and output details that would help an agent use it effectively.

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 has 100% description coverage, so parameters 'cursor' and 'tags' are well-documented in the schema itself. The description adds no additional parameter semantics, but the high schema coverage justifies the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and resource ('available project rules from promptz.dev'), making the purpose understandable. However, it doesn't differentiate this tool from its sibling 'list_prompts' or 'get_rule', which would be needed for a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_rule' or 'list_prompts'. There's no mention of prerequisites, context, or exclusions, leaving the agent with insufficient usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 4 tool updates
    • First observedget_prompt
    • First observedget_rule
    • First observedlist_prompts
    • First observedlist_rules
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.4/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: get_prompt retrieves a specific prompt, get_rule retrieves a specific rule, list_prompts lists all prompts, and list_rules lists all rules. There is no overlap or ambiguity between these four operations.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case (get_prompt, get_rule, list_prompts, list_rules). The naming is perfectly predictable and readable throughout the set.

Tool Count4/5

With 4 tools, the count is reasonable and well-scoped for a prompt management server, covering core retrieval and listing operations. It's slightly lean but appropriate for the apparent scope, lacking only minor gaps like update or delete operations.

Completeness3/5

The tool set provides good read/list coverage for prompts and rules, but there are notable gaps in CRUD operations. For example, there are no tools for creating, updating, or deleting prompts or rules, which limits full lifecycle management for the domain.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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