Click on "Deploy 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., "@skillsh-mcp search for machine learning skills"
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 (Model Context Protocol) server for searching and managing AI agent skills from skills.sh.
🔍 Search Skills: Search for skills by query term
📊 Popular Skills: Get top popular skills from leaderboard
📝 Skill Details: Get information about specific skills
💻 Install Commands: Generate install commands for skills
Related MCP server: skillsmp-mcp-server
cd skillsh-mcp
npm install
npm run buildOption A: Using claude mcp add (recommended)
claude mcp add skills-sh --scope user -- node /absolute/path/to/skillsh-mcp/dist/index.jsScopes available:
--scope local (default) — Available only to you in the current project
--scope project — Shared via .mcp.json in the project root (committed to git)
--scope user — Available globally across all your projects
Option B: Using .mcp.json file
Create or edit .mcp.json in your project root:
{
"mcpServers": {
"skills-sh": {
"command": "node",
"args": ["/absolute/path/to/skillsh-mcp/dist/index.js"],
"env": {}
}
}
}Option C: Using claude mcp add-json
claude mcp add-json skills-sh '{"command":"node","args":["/absolute/path/to/skillsh-mcp/dist/index.js"]}'Add to .cursor/mcp.json in your workspace:
{
"mcpServers": {
"skills-sh": {
"command": "node",
"args": ["${workspaceFolder}/skillsh-mcp/dist/index.js"]
}
}
}Then restart Cursor.
The server provides the following tools:
search_skillsSearch for skills on skills.sh
query (required): Search term (e.g., "mapbox", "react", "gis")
limit (optional): Maximum number of results (default: 50)
get_popular_skillsGet popular skills from the leaderboard
limit (optional): Number of results (default: 20)
timeframe (optional): "all", "trending", or "hot" (default: "all")
get_skill_detailsGet detailed information about a specific skill
owner (required): GitHub owner/username
repo (required): Repository name
skillId (required): Skill ID
get_install_commandGet the npx install command for a skill
owner (required): GitHub owner/username
repo (required): Repository name
# Install dependencies
npm install
# Build
npm run build
# Run in development mode
npm run devClient | Transport | Status |
Claude Code | stdio | ✅ Supported |
Cursor | stdio | ✅ Supported |
Claude Desktop | stdio | ✅ Supported |
Get the npx install command for a skill
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | Repository name | |
| owner | Yes | GitHub owner/username |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It does not mention whether the operation is read-only, requires authentication, what the return format is, or any side effects. The word 'get' implies a read, but this is not explicit.
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, front-loaded sentence that is concise and to the point. It contains no filler or redundant information, achieving maximum clarity with minimal words.
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 is simple with only two required parameters and no output schema. However, the description does not specify the exact return format or any error conditions. It is minimally adequate but leaves room for additional clarity.
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 both 'repo' and 'owner' clearly described. The tool description adds no additional meaning beyond what the schema already provides, 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's specific function: retrieve the npx install command for a skill. This is a distinct action from sibling tools like search_skills, get_skill_details, and get_popular_skills, making it easily distinguishable.
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 only states what it does without mentioning when it should be chosen over get_skill_details or other siblings, nor does it offer any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get popular skills from the leaderboard
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results (default: 20) | |
| timeframe | No | Timeframe: "all", "trending", or "hot" | all |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden for behavioral disclosure, but it only states the action and source. It does not disclose whether this is a read-only operation, how results are ordered, pagination behavior, or any side effects. Minimal behavioral context beyond the basic action.
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 sentence with no filler, making it highly concise. However, it is under-specified in content, leaving out relevant context that could be added without adding wordiness.
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?
This simple tool with two optional parameters and no output schema still lacks important context in the description. It does not explain return format, how 'popular' is defined, the impact of timeframe, or the overall purpose relative to other skills tools. The description is barely above a stub.
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 already has 100% coverage for both parameters (limit and timeframe) with descriptions and defaults. The description adds no parameter-specific detail, so the baseline 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?
The description states a clear action and resource: 'Get popular skills from the leaderboard.' This distinguishes it from siblings like search_skills and get_skill_details by implying a ranked leaderboard source, but it doesn't explicitly differentiate or mention what makes skills 'popular.'
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 does not mention sibling tools, scenarios where this is appropriate, or exclusions. The usage context is only implied by the phrase 'from the leaderboard.'
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 by owner/repo/skillId
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | Repository name | |
| owner | Yes | GitHub owner/username | |
| skillId | Yes | Skill ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the action without revealing response format, potential errors, authentication needs, rate limits, or any side effects. 'Get detailed information' is minimally transparent, but since it's a read operation, it's not misleading—just under-specified.
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 sentence that conveys the tool's purpose and parameters succinctly. No wasted words or redundant information; it is appropriately front-loaded with the verb and resource.
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 simple lookup tool with full parameter schema coverage and no output schema, the description provides enough context to select and invoke the tool. It states the identification method and resource type. It could be improved by hinting at what 'detailed information' includes, but that is not essential for correct invocation.
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 schema already describes all three parameters with 100% coverage. The description adds the relational context that owner/repo/skillId collectively identify the specific skill, which is a small enhancement. This meets the baseline for high schema coverage but does not go beyond basic identification semantics.
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 uses a specific verb ('Get') and resource ('detailed information about a specific skill') and clearly identifies the addressing scheme (owner/repo/skillId). This distinguishes it from sibling tools like search_skills and get_popular_skills, which focus on discovery rather than lookup of a single skill.
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 phrase 'detailed information about a specific skill' implies that this tool is for retrieving details when the identifiers are already known, as opposed to searching or browsing. However, it does not explicitly name alternatives or state when not to use it, so it falls slightly short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for skills on skills.sh by query term (e.g., "mapbox", "react", "gis")
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results (default: 50) | |
| query | Yes | Search query term |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral transparency burden. It mentions the external source (skills.sh) but does not disclose return format, pagination, rate limits, or whether results are ordered. The agent has no information about what a successful response looks like or any side effects.
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 concise sentence, front-loaded with the action 'Search for skills', and every word adds meaning. No filler or redundant information.
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 is simple with two parameters, and the description covers its core purpose. However, since there is no output schema, the description should ideally mention what the search returns (e.g., a list of skill names) to fully prepare an agent. This is a notable gap, but the tool's straightforward nature keeps it at a minimal viable level.
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 already describes both parameters (query and limit), and the description adds value by providing example query terms that clarify the expected input format. This goes beyond the schema's generic 'Search query term' description.
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 searches for skills on skills.sh using a query term, and includes concrete examples (mapbox, react, gis). This distinguishes it from sibling tools like get_skill_details and get_popular_skills, which perform different operations.
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 finding skills by term, but it does not provide explicit guidance on when to prefer this tool over siblings or when not to use it. No alternatives or exclusions are mentioned, leaving the agent to infer context.
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.
v1.0.0get_install_commandget_popular_skillsget_skill_detailssearch_skillsScored across 4 tools
Each tool has a distinct purpose: searching, fetching details, retrieving popular skills, and generating install commands. No overlap or ambiguity between them.
All tool names follow a consistent verb_noun pattern (search_skills, get_skill_details, get_popular_skills, get_install_command). The verbs 'search' and 'get' are semantically appropriate and the pattern is uniform.
With only 4 tools, the server is well-scoped for a skills directory service. Each tool earns its place and covers the core actions without unnecessary clutter.
The tool surface covers the full discovery-to-installation workflow: searching, viewing details, browsing popular items, and getting the install command. No obvious missing operations for its read-only purpose.
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