AI & Machine Learning
usefuturestack.com
Provides tools to search and explore an AI tools directory, including categories, trending tools, tool details, and a daily featured stack.
ENDPOINT 1
https://www.usefuturestack.com/api/mcp
MCP server metadata
- Name
- futurestack-mcp
- Version
- 1.0.0
Known tools 5
search_toolsSearch AI tools on FutureStack by keyword, category, role, or pricing model.
Inferred read-onlyget_tool_detailsGet comprehensive details for a specific AI tool by its unique URL slug (e.g.
Inferred read-onlylist_categoriesList all 12+ categories and audience roles supported on FutureStack.
Inferred read-onlyCONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.futurestack-mcp]
url = "https://www.usefuturestack.com/api/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"futurestack-mcp": {
"type": "http",
"url": "https://www.usefuturestack.com/api/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: futurestack-mcp
Remote MCP URL: https://www.usefuturestack.com/api/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"futurestack-mcp": {
"url": "https://www.usefuturestack.com/api/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"futurestack-mcp": {
"type": "http",
"url": "https://www.usefuturestack.com/api/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "futurestack-mcp",
"transport": "streamable-http",
"url": "https://www.usefuturestack.com/api/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
TRUST AND VERIFICATION EVIDENCE
Loading Trust v2 evidence…
Checking the associated registrable domain. The BuiltWith key remains server-side.
Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.