HyperStore
Search and inspect 6,500+ curated AI apps from the HyperStore directory.
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
claude mcp add --transport http hyperstore 'https://mcp.store.hypergpt.ai/mcp'
{
"mcpServers": {
"hyperstore": {
"type": "http",
"url": "https://mcp.store.hypergpt.ai/mcp"
}
}
}
claude mcp add --transport sse hyperstore 'https://mcp.store.hypergpt.ai/sse'
{
"mcpServers": {
"hyperstore": {
"type": "sse",
"url": "https://mcp.store.hypergpt.ai/sse"
}
}
}
hyperstore-mcpclaude mcp add hyperstore -- uvx hyperstore-mcp==0.1.1
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": [
"hyperstore-mcp==0.1.1"
]
}
}
}
ghcr.io/deficlow/hyperstore-mcp:0.1.1claude mcp add hyperstore -- docker run -i --rm ghcr.io/deficlow/hyperstore-mcp:0.1.1
{
"mcpServers": {
"hyperstore": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/deficlow/hyperstore-mcp:0.1.1"
]
}
}
}
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
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
13 tools:
| Tool | Purpose |
|---|---|
search_apps | Full-text keyword search |
ai_search | Embedding-based semantic search |
get_app | Full app detail (features, screenshots, pricing) |
list_apps | Paginated apps with filters (category, pricing) |
list_categories | Browse all 30+ categories |
category_apps | Apps within a category |
browse_apps | A-Z directory listing |
get_homepage | Trending + top categories overview |
get_alternatives | Curated alternatives to an app |
list_audiences | Audience segments (developers, lawyers, …) |
apps_for_audience | Best AI tools for an audience |
list_use_cases | Use-case taxonomies (legal-contracts, …) |
apps_for_use_case | AI tools for a use case |
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-mcp
Option B — pipx
pipx install hyperstore-mcp
hyperstore-mcp
Option C — Docker (for remote hosting)
docker run --rm -p 8080:8080 ghcr.io/deficlow/hyperstore-mcp
# Now MCP Streamable HTTP at http://localhost:8080/mcp
Option D — Hosted endpoint (no install)
Use our managed Streamable HTTP server:
https://mcp.store.hypergpt.ai/mcp
Connect 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-mcp
Cursor
.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/mcp - Authentication: 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 |
|---|---|---|
MCP_HOST | 0.0.0.0 | Bind host (http/sse transports) |
MCP_PORT | 8080 | Bind port (http/sse transports) |
LOG_LEVEL | INFO | Logging level (DEBUG, INFO, WARNING, ERROR) |
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 testing
Inspect the running server with the official MCP Inspector:
npx @modelcontextprotocol/inspector uvx hyperstore-mcp
How 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/api
License
MIT © HyperGPT
Frequently asked questions
What is HyperStore?
Search and inspect 6,500+ curated AI apps from the HyperStore directory.
How do I install HyperStore?
It runs as a remote server. In Claude Code: claude mcp add --transport http hyperstore 'https://mcp.store.hypergpt.ai/mcp'. For other clients, paste the JSON configuration from this page into their MCP settings.
Does HyperStore need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is HyperStore open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains HyperStore?
It is published by deficlow. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.