A
licenseA
qualityD
maintenanceAn MCP server for discovering Claude Code skills, plugins, and MCP servers by searching 15,000+ resources from 17 registries, GitHub, and the web with zero setup.
3
46
3
MIT
auto-skill-connector
This server provides two tools to search and install from a database of ~200k scraped Claude skills, MCP servers, and plugins.
recommend_skill(task): Performs a hybrid full-text + semantic search over the database using a short, keyword-rich task description. Returns the best matching skill's fullSKILL.mdcontent for immediate use, or a short list of options if multiple skills match equally well.install_skill(url, name?): Downloads a skill'sSKILL.mdfrom a given URL (typically returned byrecommend_skill) and installs it permanently to~/.claude/skills/<name>/SKILL.md, making it available as a/skillcommand in Claude Code across any project. An optional custom name can be provided; otherwise a default is used.
Uses Supabase as the database backend to store a large collection of Claude skills, supporting hybrid full-text and semantic search queries.
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., "@auto-skill-connectorfind a skill to summarize youtube videos"
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.
auto-skill-connector
An MCP connector that gives Claude Code / Claude Desktop access to a database
of ~200k scraped Claude skills, MCP servers, and plugins. Instead of building
a capability from scratch, Claude can search this database mid-conversation,
read a matching skill's instructions, and follow them immediately — or
install it permanently as a real /skill.
It ships two tools:
recommend_skill(task)— hybrid full-text + semantic search over the skill database. Returns the best match's fullSKILL.mdcontent (or a short list to pick from, if a few skills fit equally well).install_skill(url, name?)— downloads a skill'sSKILL.mdand saves it to~/.claude/skills/<name>/SKILL.md, so Claude Code can invoke it as a normal skill from then on, in any project.
Query embedding happens server-side (Supabase Edge Function), so this
connector only depends on mcp + httpx — no local ML runtime to install.
Install
Claude Code
claude mcp add auto-skill --scope user -- uvx --from git+https://github.com/neelavalareddy/auto-skill-connector auto-skill-mcpClaude Desktop
Add this to your claude_desktop_config.json (Settings → Developer, or find
it directly — on Windows it's usually under
%APPDATA%\Claude\claude_desktop_config.json):
{
"mcpServers": {
"auto-skill": {
"command": "uvx",
"args": ["--from", "git+https://github.com/neelavalareddy/auto-skill-connector", "auto-skill-mcp"]
}
}
}Restart Claude Desktop after editing the config.
Both require uv installed (uvx ships with
it) — no cloning or manual pip install needed.
Related MCP server: @skill-hub/mcp-server
Automatic skill suggestions (optional, Claude Code)
Want every chat message checked against the database automatically? Add the
included hooks/skill_suggest.py as a UserPromptSubmit hook: it runs on
each prompt you send, and when a skill matches, Claude is told to fetch and
apply it via recommend_skill. It fails open — errors and timeouts never
block or slow your chat.
Download
hooks/skill_suggest.pysomewhere permanent (e.g.~/.claude/hooks/skill_suggest.py).Merge this into
~/.claude/settings.json(use an absolute path on Windows, e.g.C:\\Users\\you\\.claude\\hooks\\skill_suggest.py):
{
"hooks": {
"UserPromptSubmit": [
{
"hooks": [
{
"type": "command",
"command": "python",
"args": ["~/.claude/hooks/skill_suggest.py"],
"timeout": 10
}
]
}
]
}
}Running it directly
git clone https://github.com/neelavalareddy/auto-skill-connector
cd auto-skill-connector
pip install -e .
python mcp_server.pyHow it works
The skill database lives in Supabase (Postgres + pgvector), populated by a
separate scraper that continuously crawls GitHub, npm, and the MCP registry
for Claude skills. This repo only contains the read-only connector — search
queries hit a read-only anon key (RLS grants SELECT only; no writes are
possible with it).
Available Tools
2 toolsinstall_skillA
Download a skill's SKILL.md (by url, as returned from recommend_skill) and install it into ~/.claude/skills//SKILL.md so Claude Code can invoke it as a normal /skill from now on, in any project.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| name | No |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
A4.3/5.0
Behavior3/5
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 describes the file write operation and path, but does not disclose potential side effects like overwriting existing skills, error handling, or network requirements.
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?
Single sentence packed with essential information, no unnecessary words.
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?
Given no annotations and no schema descriptions, the description covers the core workflow well. It could mention the return value (output schema exists) but the essential usage is clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds critical meaning: 'url' is the source from recommend_skill, and 'name' determines the folder name in ~/.claude/skills/. Both parameters are effectively explained.
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 downloads a SKILL.md from a URL and installs it to a specific path, distinguishing it from the sibling tool recommend_skill which returns URLs.
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?
It explains the tool is for installing skills obtained from recommend_skill, but does not explicitly state when not to use or provide alternatives beyond the sibling reference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recommend_skillA
Search the auto-skill database (~200k scraped Claude skills, MCP servers, and plugins) for the one that best matches a task, and return its full SKILL.md content so it can be read and followed immediately.
Call this whenever the user's request might already be covered by an existing packaged skill/MCP server, before building something from scratch. Pass a short, keyword-rich description of the task.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes |
TDQS
A4.5/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It discloses the database size (~200k) and composition (scraped skills, MCP servers, plugins), and states it returns full SKILL.md content. It implies a read-only operation, though it could be more explicit about no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two paragraphs: one explaining what the tool does and why, and one providing usage advice. Every sentence adds value, and the structure is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema and a single required parameter, the description covers the tool's purpose, input format, and usage context thoroughly. It includes database size and composition, making it complete for a search tool.
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 single parameter 'task' has 0% schema description coverage. The description compensates by specifying 'a short, keyword-rich description of the task,' adding meaningful guidance beyond the schema's 'Task' label.
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: it searches a database of ~200k skills and returns the full SKILL.md content. It uses specific verbs and resources, and distinguishes from the sibling tool 'install_skill' by focusing on recommendation before installation.
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 explicitly advises calling the tool when the user's request might be covered by an existing skill, before building from scratch. It also recommends passing a keyword-rich description. While it doesn't list explicit when-not cases, the guidance is clear.
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. Dates show when Glama detected each change.
2 tool updates
v0.1.0- First observed
install_skill - First observed
recommend_skill
TDQS
A4.3/5.0
Disambiguation5/5
The two tools have clearly distinct purposes: one searches and returns skill content, the other installs a skill from a URL. No overlap in functionality.
Naming Consistency5/5
Both tools follow a consistent verb_noun pattern: 'install_skill' and 'recommend_skill', making them predictable and easy to distinguish.
Tool Count3/5
With only two tools, the server feels minimal for a skill management system. While it covers the core workflow of finding and installing skills, it lacks tools for listing, updating, or removing skills, which limits its utility.
Completeness3/5
The server covers the basic find-and-install flow but is missing lifecycle operations like listing installed skills, updating, or removing them. Users may need additional tools to manage their skill set effectively.
Maintenance
ActivityMaintained
ResponsivenessSyncing
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Search verified Claude Code plugins and skills; fetch portable SKILL.md sources. Read-only.
Search the HeyClaude directory of Claude Code agents, MCP servers, skills, and tools.
Search 41,000+ agent skills, MCP servers, plugins & loops — real install counts and stars.
Quality-ranked, cross-platform directory of AI coding skills, plugins and MCP servers.
Related MCP Servers
- AlicenseAqualityCmaintenanceEnables AI assistants to discover, search, and install Claude Code Skills from SkillHub, with tools for semantic search, browsing, recommendations, and installation.5261MIT
- AlicenseNot gradedqualityCmaintenanceAn MCP server for searching, security scanning, installing, and managing skills from the SkillsMP marketplace, designed for Claude Code and other MCP-compatible clients.144MIT
- AlicenseAqualityAmaintenanceEnables AI agents to search a curated directory of Claude Code agent skills, MCP servers, and plugin marketplaces ranked by community signal.4137MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/neelavalareddy/auto-skill-connector'
If you have feedback or need assistance with the MCP directory API, please join our Discord server