Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@@skill-hub/mcp-server find skills for processing PDF files"
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.
MCP Server for SkillHub - Discover, search, and install Claude Code Skills directly from your AI assistant.
Tool | Description |
| Semantic search for skills using natural language |
| Get detailed skill information, evaluation, and content |
| Generate installation commands for bash/PowerShell |
| Browse skill catalog with filters and sorting |
| Get context-based skill recommendations |
Resource | Description |
| List of all skill categories |
| Top 10 popular skills |
| Recently added skills |
Related MCP server: Skill Loader MCP Server
Get your API Key from SkillHub Developer Dashboard
Configure Claude Code or Claude Desktop with your key
Add to ~/.claude/settings.json:
{
"mcpServers": {
"skillhub": {
"command": "npx",
"args": ["-y", "@skill-hub/mcp-server"],
"env": {
"SKILLHUB_API_KEY": "your-api-key-here"
}
}
}
}Add to your claude_desktop_config.json:
{
"mcpServers": {
"skillhub": {
"command": "npx",
"args": ["-y", "@skill-hub/mcp-server"],
"env": {
"SKILLHUB_API_KEY": "your-api-key-here"
}
}
}
}npm install -g @skill-hub/mcp-server
SKILLHUB_API_KEY=your-api-key skillhub-mcpOnce configured, you can use SkillHub directly in your AI conversations:
User: "Find me a skill for processing PDF files"
AI: [Calls search_skills] Found 3 relevant skills...User: "Tell me more about the pdf-processor skill"
AI: [Calls get_skill_detail] Here's the detailed information...User: "Install the pdf-processor skill"
AI: [Calls install_skill] Here are the installation commands...User: "Show me the top-rated skills in the 'Development' category"
AI: [Calls browse_catalog] Here are the top development skills...User: "I'm working on a code review automation project"
AI: [Calls recommend_skills] Based on your context, I recommend...Variable | Description | Required |
| Your SkillHub API Key | Yes |
| SkillHub API base URL | No (default: |
Visit skillhub.club
Sign in or create an account
Go to Developer Dashboard
Click "New Key" to generate your API key
Copy the key and add it to your MCP configuration
# Clone the repo
cd packages/mcp-server
# Install dependencies
npm install
# Run in development mode
npm run dev
# Build for production
npm run buildMIT
Browse the skill catalog with filtering and sorting options. Good for discovering skills by category or popularity.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter by category (optional) | |
| sort | No | Sort order (default: composite) | composite |
| limit | No | Number of results (1-50, default: 10) | |
| offset | No | Pagination offset (default: 0) | |
| min_score | No | Minimum quality score 0-100 (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It mentions filtering and sorting but does not describe important traits such as whether results include summary details, performance implications, or authorization needs. It is adequate but not rich.
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?
Two concise sentences with no wasted words. The description is front-loaded with the core action and immediately adds context for usage.
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?
The tool has 5 optional parameters and no output schema. The description does not mention the return format or that pagination is available (though offset/limit parameters are in the schema). It is minimally complete for a browsing tool but could be more explicit about the result shape.
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?
Schema coverage is 100%, so baseline is 3. The description adds context by linking 'category' and 'popularity' to the sort options, giving meaning beyond the schema's enum labels. This justifies above baseline.
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 action ('browse'), the resource ('skill catalog'), and the purpose ('discovering skills by category or popularity'). It implicitly distinguishes from sibling tools like search_skills (text search) and recommend_skills (personalized suggestions) by focusing on filtering/sorting for discovery.
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 tells when to use the tool ('Good for discovering skills by category or popularity'), providing clear context. However, it does not explicitly state when not to use it or name alternatives, though that awareness can be inferred from sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get detailed information about a specific skill including evaluation, pros/cons, and optionally the full SKILL.md content.
| Name | Required | Description | Default |
|---|---|---|---|
| skill_id | Yes | Skill ID or slug (e.g., 'pdf-processor' or UUID) | |
| include_content | No | Include full SKILL.md content (default: false) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations; description does not explicitly state read-only nature or any side effects, though 'get' implies non-destructive. Lacks disclosure of permissions, rate limits, or error 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?
Single, focused sentence with no unnecessary words. Every part contributes to understanding the tool's function.
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?
No output schema, so description should detail return format; it does not. Also missing error handling info. Despite having only 2 params, the description is insufficient for an agent to fully understand the response structure.
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?
Schema coverage is 100%; both parameters have descriptions. Description adds no extra meaning beyond what schema provides (e.g., 'include_content' is already described). Baseline score of 3 applies.
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?
Description clearly states the tool gets detailed information about a specific skill, listing specific aspects (evaluation, pros/cons, optional content). Distinguishes from sibling tools like search_skills (searching) and install_skill (installation).
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?
Implied usage: when needing detailed info on a specific skill. No explicit when-to-use, when-not-to-use, or alternatives provided among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Install a skill to the local filesystem. First call shows a preview, then call with confirm=true to install. Auto-detects current CLI environment (detected: claude).
| Name | Required | Description | Default |
|---|---|---|---|
| skill_id | Yes | Skill ID or slug to install | |
| agents | No | Target agents. Auto-detected: claude. Override to install for multiple agents. | |
| confirm | No | Set to true to confirm and execute installation. First call without confirm to preview. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Given no annotations, the description adequately discloses the two-step destructive behavior (preview then install) and auto-detection of agents. It explains that the first call shows a preview without installing, and confirmation is required. It does not detail error conditions or side effects like overwriting, but the core behavior is clear.
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 two sentences, front-loaded with the purpose, and provides usage guidance without any wasted words. It is appropriately sized for a simple tool.
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 mutation tool with no output schema and no annotations, the description covers the essential behavior: two-step installation, auto-detection, and parameter roles. It lacks details on what the preview returns and success confirmation, but overall it is sufficiently complete for a tool with only 3 parameters and a simple workflow.
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?
Schema description coverage is 100%, so baseline is 3. The description adds minimal new meaning beyond the parameter descriptions; it reiterates the flow and auto-detection, which are already implied in schema descriptions for 'confirm' and 'agents'.
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 installs a skill to the local filesystem, with a specific two-step process (preview then confirm). It distinguishes from sibling tools like browse_catalog or search_skills, which are read-only or information-retrieval tools.
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 explicit steps: first call for preview, then call with confirm=true to install. It mentions auto-detection of the CLI environment. However, it does not explicitly contrast with sibling tools or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get skill recommendations based on what you're working on. Uses semantic matching to find relevant skills.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes | Description of your current task or project | |
| current_skills | No | Already installed skill IDs/slugs to exclude | |
| limit | No | Number of recommendations (1-10, default: 5) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions 'semantic matching' but does not disclose potential latency, required permissions, or whether it uses external services, though no destructive behavior is implied.
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?
Two focused sentences with no extraneous content, front-loading the purpose.
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?
No output schema exists, and description does not specify the return structure (e.g., list of skill IDs with scores), which would aid agent 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?
Schema coverage is 100% with clear parameter descriptions; description adds no additional meaning beyond the schema.
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?
Clearly states verb 'Get' and resource 'skill recommendations', and distinguishes from siblings like search_skills and browse_catalog by focusing on semantic matching based on current work context.
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?
Implies usage when needing context-based recommendations, but lacks explicit comparison to search_skills for when to use one over the other.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for Claude Code Skills using natural language. Returns relevant skills based on semantic matching.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language search query (e.g., 'PDF processing', 'code review', 'git workflow') | |
| limit | No | Number of results (1-20, default: 5) | |
| category | No | Filter by category (optional) | |
| min_score | No | Minimum quality score 0-100 (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions 'semantic matching' but does not detail result ordering, pagination, or potential side effects. Adequate but minimal.
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?
Two sentence description is concise and front-loaded. No unnecessary text, though could be slightly more informative without adding length.
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 search tool with 4 parameters and no output schema, the description is adequate but lacks details about result structure or behavior. Not incomplete, but could be richer.
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?
Schema description coverage is 100% with all parameters described. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
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 action 'Search for Claude Code Skills' using natural language and semantic matching, distinguishing it from sibling tools like browse_catalog or get_skill_detail.
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 natural language queries but lacks explicit guidance on when to use versus alternatives like recommend_skills. No 'when not to use' or prerequisite info.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Each tool has a clearly distinct purpose: browsing by categories, getting detailed info, installing, recommending, and searching. No overlap that would cause confusion.
All tool names follow a consistent verb_noun pattern using underscores (e.g., browse_catalog, get_skill_detail). No mixing of conventions.
Five tools is well-scoped for a skill hub server, covering discovery, retrieval, and installation without being too few or too many.
Covers key consumer operations (browse, search, get detail, install) but lacks an uninstall or list installed tools, which is a minor gap.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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