基于Open Strategy Partners久经考验的方法论，提供一套全面的技术营销内容创建、优化和产品定位工具。这是 OSP 营销工具 MCP 服务器的 TypeScript 实现。
与原始 Python 版本相比，此 TypeScript/Node.js 实现具有显著优势：
简化安装：更少的依赖性和更直接的安装过程
跨平台兼容性：在 Windows 上无缝运行，没有常见的 Python 依赖问题
更快的性能：Node.js 通常为这种类型的服务器提供更好的性能
现代 JavaScript 生态系统：利用强大的 npm 包生态系统
更易于集成：更易于与 Web 应用程序和其他 JavaScript 工具集成
较低的资源使用率：通常需要较少的内存和系统资源
非常适合那些想要使用 OSP 营销工具而又不想处理 Python 依赖项、虚拟环境或兼容性问题的人。
Related MCP server: WithSeismic MCP
生成结构化的OSP 产品价值图，有效传达您的产品价值和定位。此工具提供：
战略标语的创建和完善
涵盖市场、技术、用户体验和业务维度的立场声明
角色、挑战和需求的角色发展
价值案例文档，包含明确的优势、挑战和解决方案
结构化层次中的特征分类
通过合理的关键词布局和 SEO 友好的结构，为网页内容创建优化的元数据。此工具可提供以下功能：
文章标题（H1）包含战略性关键词
针对搜索进行优化的元标题（50-60 个字符）
具有引人注目的价值主张的元描述（155-160 个字符）
SEO友好的URL段
搜索意图分析和优化
移动显示注意事项
应用OSP的语义编辑代码进行全面的内容审核。该系统提供：
范围和叙事结构分析
流程和可读性增强
风格和措辞优化
词汇选择和语法验证
技术准确性验证
包容性语言指导
提供前后示例的建设性反馈
系统化的方法，用于创建具有合理叙事结构和流程的高质量技术内容。本指南涵盖以下内容：
叙事结构原则和逻辑进程
流程优化和内容组织
清晰、精确的风格指南
技术准确性验证
内容类型特定指南（教程、参考文档、API 文档）
可访问性和国际化最佳实践
全面的网站内容优化系统，旨在提升搜索引擎和用户体验。本指南包含以下内容：
元内容优化策略
内容深度增强技术
跨不同查询类型的搜索意图对齐
关键词研究和集成协议
内部链接最佳实践
结构化数据实现
内容推广策略
Node.js 18 或更高版本
npm 或 yarn
您可以通过两种方式安装和使用此包：
全局安装包：
添加到您的 Claude Desktop 配置文件（ claude_desktop_config.json ）：
{
"mcpServers": {
"ai_think_gate": {
"command": "npx",
"args": [
"-y",
"@trishchuk/osp-marketing-tools-mcp"
]
}
}
}# Clone the repository
git clone https://github.com/x51xxx/osp-marketing-tools-mcp.git
cd osp-marketing-tools-mcp
# Install dependencies
npm install
# Build the project
npm run build添加到您的 Claude Desktop 配置文件（ claude_desktop_config.json ）：
{
"mcpServers": {
"osp_marketing_tools": {
"command": "node",
"args": [
"path/to/osp-marketing-tools-mcp/dist/index.js"
]
}
}
}Windows 用户须知：请务必将path/to/osp-marketing-tools-mcp替换为您计算机上osp-marketing-tools-mcp目录的实际路径。例如，如果您将仓库克隆到C:\Users\YourName\Documents\osp-marketing-tools-mcp ，则args行应如下所示：
"args": ["C:\\Users\\YourName\\Documents\\osp-marketing-tools-mcp\\dist\\index.js"]另外，请记住在路径中使用双反斜杠\\而不是单反斜杠\ 。
npm startnpm run start:sse这将在端口 3000 上启动一个 Web 服务器（可通过 PORT 环境变量配置），该服务器通过服务器发送事件 (SSE) 公开 MCP API。
一旦服务器在 HTTP/SSE 模式下运行，您就可以访问http://localhost:3000/上的 Web 界面，该界面提供了可用工具的交互式演示。
health_check - 服务器健康状态和资源可用性检查
get_editing_codes - OSP 编辑代码文档和语义内容审查使用协议
get_writing_guide - OSP 写作指南，其中包含创建高质量技术内容的原则
get_meta_guide - 用于 Web 内容元数据优化的 OSP 元信息生成器
get_value_map_positioning_guide - OSP 产品价值图生成器，用于有效的产品定位
get_on_page_seo_guide - OSP 页面 SEO 指南，用于全面内容优化
edit-content - 使用 OSP 编辑代码审查内容，以提高质量和清晰度
generate-meta - 为网页内容生成优化的元数据，并放置适当的关键词
generate-value-map - 创建结构化的 OSP 价值图，用于产品定位
apply-writing-guide - 应用 OSP 写作原则来创建技术内容
optimize-seo - 应用页面搜索引擎优化策略来优化搜索内容
要使用 OSP 编辑代码来审查内容，只需将此提示发送给 Claude（配置 MCP 服务器后）：
Review this technical content using OSP editing codes:
Kubernetes is a container orchestration platform. It handles deploying applications and scaling them as needed. There's lots of things it can do. It's really good. You should use it for your applications to make them more resilient.生成产品价值图：
Generate an OSP value map for [Product Name] focusing on [target audience] with the following key features: [list features]
Example:
Generate an OSP value map for CloudDeploy focusing on DevOps engineers with these key features:
- Automated deployment pipeline
- Infrastructure as code support
- Real-time monitoring
- Multi-cloud compatibility该服务器提供了一个 JavaScript 客户端示例，演示了如何使用服务器发送事件 (SSE) 连接到 MCP 服务器。当您以 HTTP/SSE 模式运行服务器时，您可以通过http://localhost:3000/访问该示例。
下面是一个以编程方式连接到 SSE 端点的简单示例：
// Connect to SSE endpoint
const source = new EventSource('http://localhost:3000/sse');
let sessionId;
// Listen for session ID
source.addEventListener('sessionId', (event) => {
sessionId = JSON.parse(event.data).sessionId;
console.log(`Connected with session ID: ${sessionId}`);
});
// Listen for tool responses
source.addEventListener('toolResponse', (event) => {
const response = JSON.parse(event.data);
console.log('Tool response:', response);
});
// Call a tool
async function callTool(name, args = {}) {
const response = await fetch(`http://localhost:3000/messages?sessionId=${sessionId}`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
jsonrpc: '2.0',
id: Date.now().toString(),
method: 'tools/call',
params: {
name: name,
arguments: args
}
})
});
return response.json();
}# Run in development mode (stdio)
npm run dev
# Run in development mode (HTTP/SSE)
npm run dev:sseosp-marketing-tools-mcp/
├── prompts/ # Markdown resources from OSP tools
├── public/ # Static web files for HTTP server
│ └── index.html # SSE client demo interface
├── src/
│ ├── utils/ # Utility functions
│ │ └── contentReader.ts
│ ├── tools/ # MCP tool implementations
│ │ └── index.ts
│ ├── prompts/ # MCP prompt templates
│ │ └── index.ts
│ ├── resources/ # MCP resource implementations
│ │ └── index.ts
│ ├── index.ts # Main entry point (stdio)
│ └── http.ts # HTTP/SSE server
├── dist/ # Compiled JavaScript (generated)
├── package.json
└── tsconfig.json该软件基于Open Strategy Partners开发的内容创建和优化方法，并实现了其基于 LLM 的营销工具和专业内容创建框架。
欲了解更多信息和原始资源，请访问：
本软件根据知识共享公司 (“知识共享”) 的署名-相同方式共享 4.0 国际许可进行授权。
Get the Open Strategy Partners (OSP) editing codes documentation and usage protocol for editing texts. These semantic editing marks provide a standardized framework for content review with a teaching/learning focus.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 describes what the tool returns (documentation and usage protocol) but doesn't cover important aspects like whether it's a read-only operation, potential rate limits, authentication requirements, or error handling. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with two sentences that efficiently convey the tool's purpose and the nature of the content. It's front-loaded with the main action and resource, though it could be slightly more structured by explicitly separating purpose from content characteristics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description provides adequate basic information about what the tool does. However, it lacks details about the return format (e.g., whether it's structured data, a document, or a reference), which would be helpful since there's no output schema. For a simple retrieval tool, this is minimally viable but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, which is efficient and correct for this case.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: retrieving OSP editing codes documentation and usage protocol for editing texts. It specifies the resource (OSP editing codes) and the action (get), though it doesn't explicitly differentiate from sibling tools like 'get_writing_guide' or 'get_meta_guide' beyond mentioning the specific content type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It mentions the tool's content focus (semantic editing marks for content review with teaching/learning focus) but doesn't indicate when to choose it over sibling tools like 'get_writing_guide' or 'get_on_page_seo_guide', nor does it specify any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the Open Strategy Partners (OSP) Web Content Meta Information Generation System for creating optimized article titles, meta titles, meta descriptions, and slugs for web content with proper keyword placement and search intent analysis.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 describes what the system does (generates optimized content elements) but lacks details on behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, or what the output format looks like. This is a significant gap for a tool with zero 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single run-on sentence that packs multiple concepts (system name, purpose, elements generated, and analysis features). While it conveys key information, it could be more structured and front-loaded for clarity. It's not overly verbose but could be tightened for better readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by generating optimized content with search intent analysis, and with no annotations or output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a guide, template, or generated text), how to interpret results, or any operational constraints, leaving gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does 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, which is efficient. However, it could have mentioned if any implicit inputs or context are required, but this is minor, warranting a high score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool retrieves a specific system (OSP Web Content Meta Information Generation System) for creating optimized web content elements, which is a clear purpose. However, it doesn't distinguish this from sibling tools like 'get_on_page_seo_guide' or 'get_writing_guide' that might cover overlapping SEO/content optimization areas, making it somewhat vague about its unique scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating article titles, meta titles, descriptions, and slugs with keyword placement and search intent analysis, but provides no explicit guidance on when to use this tool versus alternatives like 'get_on_page_seo_guide' or 'get_writing_guide'. There are no exclusions or prerequisites mentioned, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the Open Strategy Partners (OSP) On-Page SEO Optimization Guide for comprehensive web content optimization, covering meta content, keyword research, content depth, search intent alignment, internal linking, and structured data.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 this is a 'Get' operation which implies read-only behavior, but doesn't explicitly confirm this or mention any other behavioral traits like authentication requirements, rate limits, response format, or potential side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the tool's purpose and scope. It front-loads the core function ('Get the Open Strategy Partners (OSP) On-Page SEO Optimization Guide') and then provides useful detail about what the guide covers. Every part of the sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema and no annotations, the description provides adequate but minimal information. It tells what resource is retrieved and what topics it covers, but doesn't describe the return format, potential errors, or any operational constraints. Given the simplicity of the tool (no parameters), the description meets minimum viable standards but could be more complete regarding behavioral expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters (input schema is empty object), so there are no parameters to document. The description appropriately doesn't discuss parameters since none exist. With 100% schema description coverage and zero parameters, a baseline of 4 is appropriate as the description doesn't need to compensate for any parameter documentation gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the Open Strategy Partners (OSP) On-Page SEO Optimization Guide' with specific details about what the guide covers (meta content, keyword research, etc.). It uses a specific verb ('Get') and identifies the resource (OSP guide). However, it doesn't explicitly differentiate from sibling tools like 'get_meta_guide' or 'get_writing_guide' beyond mentioning SEO focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention when this SEO guide would be preferred over the 'get_meta_guide' or 'get_writing_guide' siblings, nor does it specify any prerequisites or contextual triggers for its use. The description simply states what the tool provides without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the Open Strategy Partners (OSP) Product Communications Value Map Generation System for Product Positioning, including taglines, position statements, personas, value cases, and feature categorization in a structured hierarchy.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 implies a read-only operation ('Get') but doesn't specify whether it requires authentication, has rate limits, returns structured vs. unstructured data, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently lists the tool's purpose and key components without redundancy. It is appropriately sized for a no-parameter tool, though it could be slightly more front-loaded by starting with the core action ('Get the OSP Product Communications Value Map Generation System').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (retrieving a structured system with multiple components), no annotations, and no output schema, the description is moderately complete. It specifies what content is included but lacks details on return format, data structure, or behavioral traits, which are needed for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (as there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate, as it efficiently avoids unnecessary detail while matching the schema's completeness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: retrieving a specific system (OSP Product Communications Value Map Generation System) with detailed content components (taglines, position statements, personas, value cases, feature categorization). It uses a specific verb ('Get') and identifies the resource, though it doesn't explicitly differentiate from sibling tools like 'get_meta_guide' or 'get_writing_guide' beyond naming the specific system.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 prerequisites, appropriate contexts, or exclusions, nor does it reference sibling tools like 'get_meta_guide' or 'get_writing_guide' to help the agent choose between them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the Open Strategy Partners (OSP) writing guide and usage protocol for creating high-quality technical content. This guide provides systematic principles for narrative structure, flow, style, and technical accuracy.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 describes what the tool returns ('writing guide and usage protocol'), but does not disclose any behavioral traits such as authentication requirements, rate limits, response format, or potential side effects. For a 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded. The first sentence clearly states the tool's purpose, and the second sentence adds useful context about the guide's content. Every sentence earns its place with no redundant or vague language, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple retrieval with no parameters) and the lack of annotations and output schema, the description is minimally adequate. It explains what the tool does but does not provide enough context for full understanding, such as response format or behavioral details. Without an output schema, the description should ideally hint at return values, but it does not, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema has 100% description coverage (though empty). With no parameters, the baseline score is 4, as there is nothing for the description to compensate for. The description does not need to add parameter semantics, so it meets expectations without extra effort.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the Open Strategy Partners (OSP) writing guide and usage protocol for creating high-quality technical content.' It specifies the verb ('Get') and resource ('writing guide and usage protocol'), and mentions the content's scope ('systematic principles for narrative structure, flow, style, and technical accuracy'). However, it does not explicitly differentiate this tool from its siblings (e.g., get_editing_codes, get_meta_guide), which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 its siblings. It mentions the guide's purpose ('for creating high-quality technical content'), but does not specify scenarios, prerequisites, or alternatives. For example, it does not clarify when to choose this over get_editing_codes or get_meta_guide, leaving usage context implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check if the server is running and can access its resources
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions checking server status and resource accessibility, but doesn't specify what constitutes 'running' or 'resources', whether this is a lightweight ping or intensive diagnostic, what authentication might be needed, or what the output format looks like. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple health check tool and front-loads the essential information ('Check if the server is running').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema, no annotations), the description provides adequate basic context about what the tool does. However, it lacks details about behavioral aspects (what 'check' entails, response format, error conditions) that would be helpful for an agent to understand the tool's operation fully, especially with no annotations to supplement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (empty schema is fully described as having no parameters). The description appropriately doesn't discuss parameters since none exist, which meets expectations for this dimension. A perfect score would require the description to explicitly note the lack of parameters, but it's reasonable to assume this from context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does 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 verbs ('check if...is running and can access') and resources ('server', 'its resources'), making it immediately understandable. However, it doesn't distinguish this health check tool from its siblings (all content/guide retrieval tools), which would require explicit differentiation 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.
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 or in what context it should be invoked. There are no prerequisites mentioned, no exclusions, and no reference to sibling tools, leaving the agent with no usage framework beyond the basic purpose statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_editing_codesget_meta_guideget_on_page_seo_guideget_value_map_positioning_guideget_writing_guidehealth_checkScored across 6 tools
Each tool has a clearly distinct purpose with no overlap: editing codes, meta guide, SEO guide, value map positioning, writing guide, and health check. The descriptions specify unique domains (e.g., semantic editing marks vs. web content optimization), making misselection unlikely.
All tools follow a consistent verb_noun pattern with 'get_' prefix for five tools and a descriptive 'health_check' for the sixth. The naming is uniform and predictable, using snake_case throughout without deviations.
Six tools are reasonable for a marketing-focused server, covering key areas like SEO, content creation, and positioning. It's slightly thin but well-scoped; each tool earns its place without redundancy or obvious gaps in the core domain.
The tools provide comprehensive guides for content creation, SEO, and positioning, but they are all 'get' operations with no create/update/delete actions. This limits agent workflows to retrieval only, leaving notable gaps for interactive or generative tasks in the marketing domain.
A Model Context Protocol server for Wix AI tools
Marketo MCP server for AI. 130 tools to operate Marketo from Claude, Cursor, or ChatGPT.
The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
