The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Worklore listing page.
An MCP (Model Context Protocol) connector for worklore.dev — it lets any MCP-capable agent (Claude, ChatGPT, Cursor, …) search worklore's developer stories, read one with its capability disclosure attached, x-ray any skill or story before running it, and — once you've signed in — record how a reproduction went or publish a story of your own.
https://worklore.dev/mcp (Streamable HTTP, JSON-RPC over POST)io.github.worklore/worklore, and Smitheryworklore stories are text your agent executes. This connector brings them — and their capability tier — into your agent, so you can find relevant work and see what it can touch before you run it. Tiers describe reach (blast radius), not virtue, and this is never a "safe" verdict. See the write-up: Stop asking "is this skill safe?" — ask "what can it do?" and the tool it wraps, skill-xray.
Capability tiers: T0 inert · T1 local · T2 network · T3 elevated (secrets / persistence / privilege) · T4 opaque (fetches/runs code at runtime).
Read-only — no sign-in needed beyond connecting:
| Tool | Arguments | Returns |
|---|---|---|
check_capability | text or url | tier (T0–T4) + sha256 + findings (file:line) + endpoints, plus behavioral red flags — capability disclosure |
get_story | slug | the story's full markdown (narrative + "Reproduce this" contract) with its capability tier + findings |
search_stories | query (optional) | matching stories (title/summary/tags/stack), each with its capability string |
suggest_for_project | context | up to 3 stories worth reproducing here, with why + tier |
Write — these act as you, and need your authenticated session:
| Tool | Arguments | Returns |
|---|---|---|
report_reproduction | slug, result (worked/partial/failed), note (optional) | the recorded reproduction. failed is a useful report and must never be inflated |
publish_story | markdown, or the parts (title, narrative, reproduce, tags, type, stack) | the published story's slug + URL. Only ever call this with the author's explicit approval of the full draft |
All six carry MCP annotations (readOnlyHint / openWorldHint / idempotentHint)
so a client can tell the user what a call will do before they approve it, and all
six declare an outputSchema and return structuredContent, so a consuming agent
can rely on shape instead of parsing prose.
Every result carries a human capability string (e.g. T0 · inert — touches nothing) so a tier code is never shown bare.
Published stories are also exposed as MCP resources under worklore://story/,
paginated, so a client that browses resources sees the library without calling a
tool. To find a specific story, use search_stories / suggest_for_project
rather than walking every page.
In Claude Code:
On claude.ai (web): Settings → Connectors → Add custom connector → name
worklore, URL https://worklore.dev/mcp. (Custom connectors need a paid plan.)
Via Smithery:
Any other MCP client: point it at https://worklore.dev/mcp (Streamable
HTTP). Your client will be walked through OAuth on first connect — it registers
itself, so there is nothing to paste and no API key to manage.
<paste a URL or the skill text>."MIT-licensed.