About Lobsters
Lobsters MCP gives AI agents access to stories and discussions from lobste.rs. It is suited to tracking community topics, with tools for trending and recent stories, tag searches, and complete comment threads.
Key features
- 01Get trending stories
- 02Get latest stories
- 03Read stories and comments
- 04Search stories by tag
Use cases
- 01Review popular community topics
- 02Track newly posted stories
- 03Explore discussions under a tag
MCP support
It exposes Lobsters story and comment tools to MCP clients. It can connect through the Pipeworx gateway or run as a local stdio MCP server.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://gateway.pipeworx.io/lobsters/mcpclaude mcp add --transport http pipeworx-io-lobsters https://gateway.pipeworx.io/lobsters/mcp{"mcpServers":{"pipeworx-io-lobsters":{"type":"http","url":"https://gateway.pipeworx.io/lobsters/mcp"}}}Open in Cursor{"servers":{"pipeworx-io-lobsters":{"type":"http","url":"https://gateway.pipeworx.io/lobsters/mcp"}}}Open in VS Code{"mcpServers":{"pipeworx-io-lobsters":{"type":"http","url":"https://gateway.pipeworx.io/lobsters/mcp"}}}{"mcpServers":{"pipeworx-io-lobsters":{"serverUrl":"https://gateway.pipeworx.io/lobsters/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
45| Parameter | Type | Required | Description |
|---|---|---|---|
| q | string | No | Alias for question. |
| ask | string | No | Alias for question. |
| text | string | No | Alias for question. |
| input | string | No | Alias for question. |
| packs | array | No | OPTIONAL. Restrict routing to these pack slugs (e.g. ["sec-form-d","sec-13f"]) — the router then picks only from tools in those packs. Omit for the default full-catalog routing. Slugs come from list_packs / search_packs / https://pipeworx.io/directory; unlisted or unknown slugs are ignored and named in _meta.pack_scope.ignored, and if none of them resolves the question is routed across the whole catalog with _meta.pack_scope.full_catalog:true (never an empty answer). |
| query | string | No | Alias for question. |
| prompt | string | No | Alias for question. |
| message | string | No | Alias for question. |
| question | string | Yes | Your question or request in natural language. Accepts query, q, prompt, text, input, ask, message as aliases. |
Details
From the project READMEmcp-lobsters
Lobsters MCP — stories and discussions from lobste.rs
Part of Pipeworx — an MCP gateway connecting AI agents to 1882+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.
Tools
| Tool | Description |
|---|---|
get_hottest | Get trending stories from Lobsters. Returns title, URL, score, comment count, and tags for each story. |
get_newest | Get latest stories posted to Lobsters. Returns title, URL, publication time, score, and tags for each story. |
get_story | Fetch a single story and all its comments by ID (e.g., "abc123"). Returns title, URL, text, score, and nested comment threads. |
get_tag | Search stories by tag (e.g., "rust", "programming", "security"). Returns matching stories with titles, URLs, scores, and tags. |
Quick Start
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"lobsters": {
"url": "https://gateway.pipeworx.io/lobsters/mcp"
}
}
}
What this endpoint actually serves
tools/list at https://gateway.pipeworx.io/lobsters/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Both URLs reach the same gateway and the same 1882+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
No MCP client? Call it over HTTP
curl -X POST https://gateway.pipeworx.io/v1/tools/get_hottest \
-H 'Content-Type: application/json' \
-d '{}'
No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/get_hottest. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.
Standalone (no gateway account)
This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:
{
"mcpServers": {
"lobsters": {
"command": "npx",
"args": ["-y", "@pipeworx/mcp-lobsters"]
}
}
}
Or run it directly to confirm it starts:
npx -y @pipeworx/mcp-lobsters
It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call
for only this pack's tools — none of the shared meta-tools the gateway
connection above adds. Same source, same tools, no ask_pipeworx routing.
Using with ask_pipeworx
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Lobsters data" })
The gateway picks the right tool and fills the arguments automatically.
More
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.