HyperStore
Search and inspect 6,500+ curated AI apps from the HyperStore directory.
Open source Repository Open in the app JSON README (API)
About
Search and inspect 6,500+ curated AI apps from the HyperStore directory.
Details
- Kind
- MCP servers
- Topic
- Files & documents
- Publisher
- deficlow
- Origin
- official
- Category
- ferramentas
- Transport
- http
- Version
- 0.1.1
- Stars
- 1
- Last push
- 2026-06-20T15:16:11Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 03:02:41
- Updated
- 2026-08-29 03:02:41
- Origin id
io.github.deficlow/hyperstore-mcp
README
# HyperStore MCP
<!-- mcp-name: io.github.deficlow/hyperstore-mcp -->
> Plug 6,500+ AI apps into any LLM via the [Model Context Protocol](https://modelcontextprotocol.io).
[](https://pypi.org/project/hyperstore-mcp/)
[](https://glama.ai/mcp/servers/deficlow/HyperStore-MCP)
[](https://smithery.ai/server/deficlow/hyperstore)
[](https://registry.modelcontextprotocol.io/v0/servers?search=io.github.deficlow/hyperstore-mcp)
[](https://github.com/deficlow/HyperStore-MCP/actions/workflows/ci.yml)
[](LICENSE)
**HyperStore** is a curated directory of 6,500+ AI applications, developed by [HyperGPT](https://hypergpt.ai).
This MCP server exposes the [HyperStore](https://store.hypergpt.ai) 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 app
- `hyperstore://category/{slug}` — top apps in a category
- `hyperstore://catalog` — full category index
**3 prompts:**
- `find_tool_for_task` — guided discovery for a task
- `compare_apps` — side-by-side app comparison
- `discover_category` — explore a topic
---
## Install
### Option A — `uvx` (zero install, recommended)
Requires [uv](https://docs.astral.sh/uv/). One command and you're done:
```bash
uvx hyperstore-mcp
```
### Option B — `pipx`
```bash
pipx install hyperstore-mcp
hyperstore-mcp
```
### Option C — Docker (for remote hosting)
```bash
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):
```json
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}
```
Restart Claude → tools appear in the 🛠 menu.
### Claude Code
```bash
claude mcp add hyperstore -- uvx hyperstore-mcp
```
### Cursor
`.cursor/mcp.json` (project) or `~/.cursor/mcp.json` (global):
```json
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}
```
### Windsurf
`~/.codeium/windsurf/mcp_config.json`:
```json
{
"mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}
```
### Cline (VS Code)
`settings.json`:
```json
{
"cline.mcpServers": {
"hyperstore": {
"command": "uvx",
"args": ["hyperstore-mcp"]
}
}
}
```
### Zed
`~/.config/zed/settings.json`:
```json
{
"context_servers": {
"hyperstore": {
"command": {
"path": "uvx",
"args": ["hyperstore-mcp"]
}
}
}
}
```
### Gemini CLI
`~/.gemini/settings.json`:
```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
```python
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
```python
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/`](examples/) for ready-to-paste configs for every supported client.
---
## Self-hosting
For self-hosting, use the [Docker image](#option-c--docker-for-remote-hosting).
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`](.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
```bash
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**:
```bash
npx @modelcontextprotocol/inspector uvx hyperstore-mcp
```
---
## How it works
HyperStore MCP is a thin async wrapper around the [HyperStore](https://store.hypergpt.ai) 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](https://hypergpt.ai)