HyperStore MCP
HyperStore MCP gives you access to a curated directory of 6,500+ AI applications, letting any MCP-compatible LLM client discover, search, browse, and compare AI tools.
Tools
search_apps— Keyword-based full-text search returning name, slug, description, pricing, and ratingai_search— Semantic/embedding-based natural language search (e.g. "something like Midjourney but free"), returning up to 12 ranked resultsget_app— Full details for a specific app by slug: long description, features, screenshots, pricing, rating, and website URLlist_apps— Paginated listing with optional filters for category, pricing model, and keyword, sorted by popularitylist_categories— All 30+ categories with app countscategory_apps— Apps within a specific category, optionally filtered by pricingbrowse_apps— Alphabetical A–Z directory browsing by starting letter (or#for digits/symbols)get_homepage— Trending apps, top categories, and catalog overview/stats
Resources
hyperstore://app/{slug}— Markdown rendering of an app's detail pagehyperstore://category/{slug}— Top apps in a given categoryhyperstore://catalog— Full category index
Prompts
find_tool_for_task— Guided discovery to find the right AI tool for a specific taskcompare_apps— Side-by-side comparison of multiple appsdiscover_category— Explore a topic or category of AI tools
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., "@HyperStore MCPFind me a free AI tool that summarises PDFs."
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.
HyperStore MCP
Plug 6,500+ AI apps into any LLM via the Model Context Protocol.
HyperStore is a curated directory of 6,500+ AI applications, developed by HyperGPT. This MCP server exposes the HyperStore catalog to any LLM client — Claude, ChatGPT, Cursor, Windsurf, Cline, Zed, Gemini, and anything else that speaks MCP.
Ask your LLM:
"Find me a free AI tool that summarises PDFs." "Compare ChatGPT, Claude, and Gemini side-by-side." "Show me the top 5 image-generation apps with an API."
The LLM calls HyperStore MCP behind the scenes and answers with up-to-date, curated results.
What you get
8 tools:
Tool | Purpose |
| Full-text keyword search |
| Embedding-based semantic search |
| Full app detail (features, screenshots, pricing) |
| Paginated apps with filters (category, pricing) |
| Browse all 30+ categories |
| Apps within a category |
| A-Z directory listing |
| Trending + top categories overview |
3 resources:
hyperstore://app/{slug}— markdown rendering of any apphyperstore://category/{slug}— top apps in a categoryhyperstore://catalog— full category index
3 prompts:
find_tool_for_task— guided discovery for a taskcompare_apps— side-by-side app comparisondiscover_category— explore a topic
Install
Option A — uvx (zero install, recommended)
Requires uv. One command and you're done:
uvx hyperstore-mcpOption B — pipx
pipx install hyperstore-mcp
hyperstore-mcpOption C — Docker (for remote hosting)
docker run --rm -p 8080:8080 ghcr.io/deficlow/hyperstore-mcp
# Now MCP Streamable HTTP at http://localhost:8080/mcpOption D — Hosted endpoint (no install)
Use our managed Streamable HTTP server:
https://mcp.store.hypergpt.ai/mcpConnect from your LLM client
Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json
(macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}Restart Claude → tools appear in the 🛠 menu.
Claude Code
claude mcp add hyperstore -- uvx hyperstore-mcpCursor
.cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}Windsurf
~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}Cline (VS Code)
settings.json:
{
"cline.mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}Zed
~/.config/zed/settings.json:
{
"context_servers": {
"hyperstore": {
"command": {
"path": "uvx",
"args": ["hyperstore-mcp"]
}
}
}
}Gemini CLI
~/.gemini/settings.json:
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}ChatGPT (Pro / Team / Enterprise)
Settings → Connectors → Add custom connector:
Name: HyperStore
MCP Server URL:
https://mcp.store.hypergpt.ai/mcpAuthentication: None
OpenAI Responses API
from openai import OpenAI
client = OpenAI()
response = client.responses.create(
model="gpt-4.1",
tools=[{
"type": "mcp",
"server_label": "hyperstore",
"server_url": "https://mcp.store.hypergpt.ai/mcp",
"require_approval": "never",
}],
input="Find me 3 free AI tools for writing unit tests.",
)
print(response.output_text)Anthropic Messages API
from anthropic import Anthropic
client = Anthropic()
response = client.messages.create(
model="claude-opus-4-7",
max_tokens=1024,
mcp_servers=[{
"type": "url",
"url": "https://mcp.store.hypergpt.ai/mcp",
"name": "hyperstore",
}],
messages=[{"role": "user", "content": "Top 5 AI image generators?"}],
)See examples/ for ready-to-paste configs for every supported client.
Self-hosting
For self-hosting, use the Docker image.
For direct invocation without Docker, the CLI accepts --transport http|sse
(see hyperstore-mcp --help).
Configuration
When self-hosting, these environment variables can be set
(see .env.example for the full list):
Variable | Default | Purpose |
|
| Bind host (http/sse transports) |
|
| Bind port (http/sse transports) |
|
| Logging level ( |
Development
git clone https://github.com/deficlow/HyperStore-MCP
cd HyperStore-MCP
uv sync --all-extras
uv run pytest
uv run hyperstore-mcp # stdio mode for local testingInspect the running server with the official MCP Inspector:
npx @modelcontextprotocol/inspector uvx hyperstore-mcpHow it works
HyperStore MCP is a thin async wrapper around the HyperStore public REST API. It is read-only — no credentials, no writes, no PII. The same data that powers the website powers the MCP server. Updates land in your LLM the moment they land on the site.
LLM client ──MCP──▶ hyperstore-mcp ──HTTPS──▶ store.hypergpt.ai/apiLicense
MIT © HyperGPT
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