ไธญๆ | English
MCP (Model Context Protocol) Server for skill4agent - Search, view, and install AI skills in AI conversations.
Provides the following capabilities through the MCP protocol:
๐ Search Skills - Search AI skills by keyword, with optional category filtering
๐ Get Details - View complete skill documentation (SKILL.md)
๐ฆ Installation Info - Get download links and installation commands for skills
Related MCP server: aiskillstore
npm install -g @skill4agent/mcp-serverOr run directly with npx:
npx @skill4agent/mcp-serverAdd the following to your Claude Desktop configuration file:
{
"mcpServers": {
"skill4agent": {
"command": "npx",
"args": ["-y", "@skill4agent/mcp-server"]
}
}
}To use a custom API endpoint, add the env configuration:
{
"mcpServers": {
"skill4agent": {
"command": "npx",
"args": ["-y", "@skill4agent/mcp-server"],
"env": {
"SKILL4AGENT_API_URL": "https://your-custom-domain.com/api/mcp"
}
}
}
}Search for AI skills.
Parameters:
keyword (required): Search keyword
categories (optional): Category filter, supports both English and Chinese
limit (optional): Limit the number of results, default is 10, maximum is 100
Example:
{
"keyword": "React",
"categories": ["Frontend Development"],
"limit": 5
}Get detailed information about a specific skill.
Parameters:
skillId (required): Skill ID, obtained from the search_skills tool results
Example:
{
"skillId": "frontend-design--anthropics-skills"
}Get installation information for a skill.
Parameters:
skillId (required): Skill ID
Example:
{
"skillId": "frontend-design--anthropics-skills"
}Variable | Description | Default |
| skill4agent API endpoint |
|
# Install dependencies
npm install
# Build
npm run build
# Development mode (hot reload)
npm run dev
# Run directly
node dist/index.js@skill4agent/mcp-server/
โโโ src/
โ โโโ index.ts # Entry point
โ โโโ server.ts # MCP Server main logic
โ โโโ api/
โ โ โโโ client.ts # API client
โ โโโ tools/
โ โโโ search.ts # search_skills tool
โ โโโ detail.ts # get_skill tool
โ โโโ install.ts # install_skill tool
โโโ package.json
โโโ tsconfig.json
โโโ README.mdMIT
Get detailed information about a skill, including the complete SKILL.md content.
Use cases:
When you want to learn detailed information about a skill
When you need to view the core documentation (SKILL.md) of a skill
Before recommending or installing a skill, you need to confirm the detailed information to analyze whether it meets the requirements
| Name | Required | Description | Default |
|---|---|---|---|
| skillId | Yes | The skill ID to query. Can be obtained from the results returned by the search_skills tool. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While it mentions retrieving 'detailed information' and 'SKILL.md content', it doesn't disclose behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, error conditions, or what format the information is returned in. 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 appropriately sized with a clear purpose statement followed by bullet-pointed use cases. Every sentence earns its place by providing specific guidance, though the third use case could be slightly more concise by combining ideas about 'recommending or installing'.
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 moderate complexity (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers purpose and usage well, but lacks behavioral transparency about how the tool operates and what it returns. Without annotations or output schema, the description should do more to explain the tool's behavior and response format.
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% (the single parameter 'skillId' is fully described in the schema), so the baseline is 3. The description doesn't add any parameter-specific information beyond what the schema already provides about obtaining skillId from 'search_skills' results.
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 verb 'Get' and resource 'detailed information about a skill', specifically mentioning 'complete SKILL.md content'. It distinguishes from sibling tools like 'search_skills' (which finds skills) and 'install_skill' (which installs them) by focusing on retrieving detailed documentation for a specific 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 'Use cases' section provides clear context for when to use this tool: to learn detailed information, view core documentation, or confirm details before recommending/installing. However, it doesn't explicitly state when NOT to use it (e.g., for finding skills vs. getting details) or name alternatives like 'search_skills' for discovery purposes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get installation methods for a skill.
Use cases:
When you need to install a skill
| Name | Required | Description | Default |
|---|---|---|---|
| skillId | Yes | The skill ID to install. Can be obtained from the results returned by the search_skills or get_skill tool. |
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. The description mentions 'Get installation methods' but does not specify what these methods entail (e.g., download links, instructions, permissions required), whether it's a read-only operation, or any rate limits. It adds minimal context beyond the basic purpose, leaving behavioral traits unclear.
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 brief and front-loaded with the main purpose, followed by a use case. It avoids unnecessary details, but the use case is somewhat redundant with the purpose statement ('Get installation methods' vs. 'When you need to install a skill'). Overall, it is efficient with minor room for improvement.
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 no annotations, no output schema, and a single parameter with full schema coverage, the description is incomplete. It lacks details on what 'installation methods' include (e.g., formats, steps), behavioral aspects like safety or permissions, and how results are structured. For a tool that presumably provides actionable information, this is inadequate.
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 100% description coverage, with 'skillId' documented as 'The skill ID to install. Can be obtained from the results returned by the search_skills or get_skill tool.' The description does not add any additional meaning beyond this schema, so it meets the baseline of 3 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Get installation methods for a skill', which clarifies the verb ('Get') and resource ('installation methods for a skill'). However, it does not distinguish from sibling tools like 'get_skill' or 'search_skills', which might also relate to skills but serve different purposes (e.g., retrieving skill details or searching for skills). The purpose is clear but lacks sibling differentiation.
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 includes 'Use cases: - When you need to install a skill', which implies usage context. However, it does not explicitly state when to use this tool versus alternatives like 'get_skill' or 'search_skills', nor does it provide exclusions or prerequisites. The guidance is implied but incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for Skills by keyword, with optional category filtering. Returns a list of matching skills.
Use cases:
When looking for skills in a specific domain
When unsure what skill is needed but have a general direction
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | Search keyword. Can be English, Chinese, or mixed. (e.g., "React", "n8n-workflow", "frontend development", "copywriting", "langchain docs") | |
| categories | No | Optional category filter. Supports both English and Chinese category names. Can pass multiple categories. (e.g., ["Frontend Development", "AI & Machine Learning"]) | |
| limit | No | Limit the number of results returned. Default is 10, maximum is 100. Set according to your needs to avoid returning too many results. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool 'Returns a list of matching skills' which is basic behavioral information. However, it doesn't disclose important traits like whether this is a read-only operation (implied but not stated), pagination behavior, rate limits, authentication requirements, or what happens with no matches. The description adds some value but lacks comprehensive behavioral context for a search tool.
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 with two clear sections: a purpose statement and use cases. Both sentences earn their place by providing distinct value. It could be slightly more concise by integrating the use cases into the main statement, but overall it's well-structured and front-loaded with the core functionality.
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 3 parameters with 100% schema coverage but no annotations and no output schema, the description provides adequate basic context but has gaps. It explains what the tool does and when to use it, but doesn't address behavioral aspects like response format, error conditions, or performance characteristics. For a search tool with no output schema, more detail about return values would be helpful.
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 the schema already fully documents all 3 parameters (keyword, categories, limit). The description mentions 'keyword' and 'category filtering' but doesn't add meaningful semantic context beyond what's in the schema descriptions. The baseline is 3 when schema does the heavy lifting, and the description doesn't compensate with additional parameter insights.
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: 'Search for Skills by keyword, with optional category filtering. Returns a list of matching skills.' This includes a specific verb ('Search'), resource ('Skills'), and scope ('by keyword, with optional category filtering'). It distinguishes from sibling tools get_skill (likely retrieves a single skill) and install_skill (likely installs a 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 description provides clear usage contexts with 'Use cases' section: 'When looking for skills in a specific domain' and 'When unsure what skill is needed but have a general direction.' This gives good guidance on when to use the tool. However, it doesn't explicitly state when NOT to use it or mention alternatives (like using get_skill for known skill IDs).
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. Dates show when Glama detected each change.
v0.1.3get_skillinstall_skillsearch_skillsEach tool has a clearly distinct purpose with no overlap: get_skill retrieves detailed information, install_skill provides installation methods, and search_skills finds skills by keyword/category. The descriptions reinforce these distinct roles, making misselection unlikely.
All tools follow a consistent verb_noun pattern with snake_case (get_skill, install_skill, search_skills). The naming is predictable and readable, with verbs that accurately reflect each tool's function without deviation.
With only 3 tools, the set feels thin for a skill management server, as it lacks operations like updating, deleting, or managing skill configurations. While the tools cover basic discovery and installation, the scope suggests more functionality would be expected for a complete skill lifecycle.
The tool surface is significantly incomplete for skill management, missing essential CRUD operations such as create_skill, update_skill, and delete_skill. Agents will hit dead ends when trying to modify or remove skills, limiting the server's utility beyond basic lookup and installation.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Hosted MCP server for live public-data APIs and Skills for AI agents.
Search and discover Agent Skills from the skills.sh registry. Powered by HAPI MCP server.
Search & install 6,500+ AI agent skills from skills-hub.ai inside any MCP tool.
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