Which integrations are available for this server?

Uses Node.js runtime environment for executing the MCP server implementation Distributed and installed through npm package manager for easy deployment

How do I use Semantic Pen MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Semantic Pen MCP Server create an article about AI content marketing strategies for 2024" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Semantic Pen MCP Server

by pushkarsingh32

Overview Schema Source Related Servers Discussions Admin

JavaScript

Remote

Semantic Pen MCP Server

The official MCP server for Semantic Pen - an advanced AI article generator and SEO content writer. Create, manage, and optimize SEO-friendly articles directly from Claude Code and Cursor with powerful AI automation.

Quick Setup (Recommended)

Just add this to your MCP configuration - no installation required!

One-Click Install for Cursor

⚠️ Important: After clicking the button above, you'll need to replace your-api-key-here with your actual Semantic Pen API key in the Cursor settings.

The button automatically adds this configuration to your Cursor MCP settings:

{
  "command": "npx",
  "args": ["-y", "semantic-pen-mcp-server@latest"],
  "env": {
    "SEMANTIC_PEN_API_KEY": "your-api-key-here"
  }
}

You just need to replace the API key placeholder with your actual key.

For Claude Code

Add to your ~/.config/claude-code/settings.json:

{
  "mcpServers": {
    "semantic-pen": {
      "command": "npx",
      "args": ["-y", "semantic-pen-mcp-server@latest"],
      "env": {
        "SEMANTIC_PEN_API_KEY": "your-api-key-here"
      }
    }
  }
}

For Cursor

Add to your Cursor MCP settings:

{
  "mcpServers": {
    "semantic-pen": {
      "command": "npx",
      "args": ["-y", "semantic-pen-mcp-server@latest"],
      "env": {
        "SEMANTIC_PEN_API_KEY": "your-api-key-here"
      }
    }
  }
}

Replace your-api-key-here with your actual Semantic Pen API key.

For Windsurf

Add to your ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "semantic-pen": {
      "command": "npx",
      "args": ["-y", "semantic-pen-mcp-server@latest"],
      "env": {
        "SEMANTIC_PEN_API_KEY": "your-api-key-here"
      }
    }
  }
}

Then restart Windsurf to load the new MCP server. Access through Cascade → Configure (hammer icon).

Related MCP server: Publora MCP Server

Features

🤖 AI-Powered Article Creation - Generate SEO-optimized articles with advanced AI automation
📊 SEO Content Optimization - Built-in keyword targeting and SEO best practices
📋 Content Project Management - Organize and manage your AI writing projects efficiently
🔍 Smart Content Search - Find and filter articles across projects instantly
⚡ Automated Workflow - Streamline your content creation process with AI automation
📄 Full Content Access - Retrieve complete article HTML ready for publishing
🔑 Seamless Authentication - Automatic API verification for hassle-free setup

Available Tools

`get_projects`

Get all your projects from the article queue

No parameters required

`get_project_articles`

Get all articles from a specific project

projectId (string): The project ID to get articles from

`search_projects`

Search projects by name

projectName (string): The project name to search for (partial match)

`create_article`

Generate SEO-optimized AI articles with advanced customization

targetArticleTopic (string): The article topic/title for AI content generation
targetKeyword (string, optional): Primary SEO keyword for optimization
wordCount (number, optional): Target word count for content length (default: 1000)
language (string, optional): Content language (default: English)
articleType (string, optional): Article format type (default: Article)
toneOfVoice (string, optional): Writing tone and style (default: Professional)

`get_article`

Get a specific article by ID with full content

articleId (string): The ID of the article to retrieve

Example Usage

Browse Content Projects: Use get_projects to view your AI article generation projects
Explore Project Content: Use get_project_articles to see all AI-generated articles in a specific project
Generate AI Articles: Use create_article with topics like "AI Content Marketing Strategies for 2024"
Access Generated Content: Use get_article to retrieve your SEO-optimized article content ready for publishing

Getting Your API Key

Visit SemanticPen.com - Your AI article writing platform
Create your account or log in to access the AI content generator
Navigate to API settings to generate your content automation key
Copy the API key and configure it for seamless AI article generation

Manual Installation (Alternative)

If you prefer to install manually:

npm install -g semantic-pen-mcp-server

Then use in your MCP config:

{
  "command": "semantic-pen-mcp",
  "env": {
    "SEMANTIC_PEN_API_KEY": "your-api-key-here"
  }
}

Troubleshooting

"API key not configured": Make sure SEMANTIC_PEN_API_KEY is set in the env section
"API key verification failed": Check that your API key is valid and active
Server not starting: Ensure you have Node.js 18+ installed

Support

For issues or questions:

Visit SemanticPen.com for support
Check your API key is valid and has sufficient credits
Ensure stable internet connection for API calls

Available Tools

5 tools

create_articleB

Create a new article

ParametersJSON Schema

Name	Required	Description	Default
`targetArticleTopic`	Yes	The topic/title for the article
`targetKeyword`	No	Target SEO keyword for the article (optional)
`wordCount`	No	Target word count (default: 1000)
`language`	No	Language for the article (default: English)	English
`articleType`	No	Type of article (default: Article)	Article
`toneOfVoice`	No	Tone of voice (default: Professional)	Professional

TDQS

B3.2/5.0

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 only says 'Create a new article,' which implies a write operation, but fails to disclose side effects, authentication needs, rate limits, or what the response contains. For a mutation 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?

The description is a single, front-loaded sentence with no waste. It is concise and to the point.

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 6 parameters, no output schema, and no annotations. The description fails to explain return values, associations (e.g., project membership), or any caveats. While it covers the basic purpose, it is incomplete for an agent to fully understand the tool's behavior.

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%, and all parameters have meaningful descriptions with defaults. The description itself adds no parameter-level detail, but since the schema fully documents them, the baseline score of 3 is appropriate.

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 'Create a new article' uses a specific verb and resource, clearly indicating the action and object. It distinguishes itself from sibling tools (get_projects, get_project_articles, search_projects, get_article) as the only creation tool.

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, no mention of prerequisites, context, or exclusions. It merely states the action without any situational framing.

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

get_articleA

Get a specific article by ID with full content

ParametersJSON Schema

Name	Required	Description	Default
`articleId`	Yes	The ID of the article to retrieve

TDQS

A4/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds that the tool returns 'full content', which is useful beyond the name, but it does not mention error handling (e.g., 404 if article not found), permission requirements, or response structure. For a read-only operation this is somewhat acceptable, but deeper context would improve 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 sentence, front-loaded, and contains no wasted words. It efficiently conveys the core action, target, and result in a compact form.

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?

For a low-complexity tool with one parameter and no output schema, the description provides sufficient context to select and invoke it correctly. It clarifies that the response includes the full article content, which is the key missing piece an agent would need. It could add error behavior details, but given the simplicity and sibling context, it is mostly complete.

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 already describes the only parameter (articleId) with 100% coverage. The description merely repeats 'by ID' and adds no additional meaning about the parameter's format, constraints, or behavior. Since schema coverage is high, the baseline score of 3 is appropriate.

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 action ('Get'), the resource ('a specific article'), and the scope ('by ID with full content'). It distinguishes from sibling tools like get_project_articles (which likely retrieves articles belonging to a project) and search_projects (which searches projects), making its purpose precise.

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 implies the proper use case: retrieving a full article when you already have its ID. It does not explicitly mention alternatives or exclusions, but the sibling tool names provide context. The phrase 'by ID' signals that this is for targeted retrieval rather than listing or searching, offering clear context without explicit when-not-to-use directions.

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

get_project_articlesA

Get all articles from a specific project by project ID

ParametersJSON Schema

Name	Required	Description	Default
`projectId`	Yes	The project ID to get articles from

TDQS

A3.6/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states what the tool does but reveals no additional behavior such as auth requirements, pagination, error handling, or result format. For a read operation, some transparency about these aspects would be expected.

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, direct sentence with no filler or redundant words. Every word contributes to the meaning, making it highly efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is largely sufficient: it names the input and the expected result ('all articles'). However, the lack of behavioral and usage guidance slightly reduces completeness, preventing a perfect score.

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 schema already fully describes the single parameter 'projectId' with a clear description. The tool description adds minimal extra meaning beyond restating the parameter's role. Since schema coverage is 100%, the baseline is 3, and the description does not enhance parameter understanding beyond the schema.

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 action ('Get all articles'), the resource ('articles'), and the scope ('from a specific project by project ID'). It distinguishes itself from sibling tools like 'get_projects' (which lists projects) and 'get_article' (which likely retrieves a single article).

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 when you have a project ID and need all its articles, but it does not explicitly contrast with sibling tools or state when not to use this tool. The context is sufficient for a simple case, but no alternatives or exclusions are mentioned.

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

get_projectsA

Get all projects from your article queue

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It implies a read-only operation via 'Get' and defines the scope as 'all projects from your article queue', but it does not disclose potential caveats like whether archived projects are included, pagination, or limits. This is adequate for a simple read tool but lacks rich behavioral context.

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, focused sentence that gets straight to the point with no wasted words. It is perfectly concise for a simple list-all tool.

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?

For a parameterless tool with no output schema, the description provides sufficient context: it states what is returned (all projects) and the source scope. While it does not describe the return format, the plural 'projects' implies a list, making it reasonably complete. However, adding a note about what a 'project' is might improve completeness.

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?

The tool has zero parameters and the schema coverage is 100%, so the description does not need to explain parameter meanings. Per the rubric, a baseline of 4 is appropriate when there are no params.

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 purpose: to retrieve all projects within a specific scope ('your article queue'). The verb 'Get' and plural 'projects' make it distinct from sibling tools like 'search_projects' (which implies filtering) and 'get_project_articles' (which targets articles, not projects).

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 'search_projects'. It does not explicitly mention exclusions or prerequisites, leaving the agent to infer that this is the go-to for listing all projects.

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

search_projectsB

Search projects by name

ParametersJSON Schema

Name	Required	Description	Default
`projectName`	Yes	The project name to search for (partial match)

TDQS

B3/5.0

Behavior1/5

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

With no annotations, the description must disclose behavioral traits, but it only restates the tool's name. It does not mention that the search is read-only, whether it returns matches or a single result, pagination, or matching behavior beyond what the schema's 'partial match' note provides (which is in the schema, not the description).

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 four-word sentence, leaving no wasted words. It is appropriately concise for the minimal information it conveys, though its brevity contributes to lack of context.

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?

For a simple search tool with no output schema, the description is insufficiently complete. It does not indicate whether the result is a list of matching projects, their structure, or how the search behaves. It also lacks any usage context relative to sibling tools, making it difficult for an agent to fully understand the tool's role.

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% with a clear parameter description ('partial match'). The tool description adds no additional semantic meaning beyond repeating the parameter name, so the baseline score of 3 is appropriate.

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 a specific verb (search) and resource (projects) with a scope (by name), distinguishing it from sibling tools like get_projects which likely fetches projects without searching. Though terse, it unambiguously conveys the tool's core function.

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 rather than get_projects or other siblings. It does not mention alternatives, prerequisites, or contexts where this search is preferred.

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.

5 tool updatesAug 18, 2025
- First observedcreate_article
- First observedget_article
- First observedget_project_articles
- First observedget_projects
- First observedsearch_projects

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

B3.3/5.0

Scored 2026-04-18 08:55 across 5 tools

Disambiguation4/5

Most tools have distinct purposes, but 'get_projects' and 'search_projects' could cause some confusion as both retrieve project information, though 'search_projects' adds filtering by name. The article-related tools (create_article, get_article, get_project_articles) are clearly differentiated by their specific actions and scopes.

Naming Consistency5/5

All tools follow a consistent verb_noun naming pattern (e.g., create_article, get_article, get_project_articles, get_projects, search_projects). The structure is uniform throughout, using snake_case and clear action-object pairs, making the tool set predictable and easy to understand.

Tool Count5/5

With 5 tools, the server is well-scoped for managing articles and projects, covering core operations without bloat. Each tool serves a clear purpose, such as creation, retrieval, and listing, which aligns with typical CRUD needs for this domain.

Completeness3/5

The tool set covers basic retrieval and creation for articles and projects, but there are notable gaps in update and delete operations. For example, there is no tool to update or delete articles or projects, which could limit agent workflows that require full lifecycle management.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

Need Help?

Reddit Discussion

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Appeared in Searches

A content research and creation service for article writing with SEO optimization

Semantic Pen MCP Server

Quick Setup (Recommended)

One-Click Install for Cursor

For Claude Code

For Cursor

For Windsurf

Features

Available Tools

get_projects

get_project_articles

search_projects

create_article

get_article

Example Usage

Getting Your API Key

Manual Installation (Alternative)

Troubleshooting

Support

Available Tools

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

PostIdentity MCP Serverofficial

Publora MCP Serverofficial

Appeared in Searches

`get_projects`

`get_project_articles`

`search_projects`

`create_article`

`get_article`