Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Search worklore stories and x-ray any skill or story capability tier (T0-T4) before you run it.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
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Funciona en Claude para web, escritorio y móvil:
https://worklore.dev/mcpEjecuta esto en tu terminal
claude mcp add --transport http worklore https://worklore.dev/mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"worklore": {
"url": "https://worklore.dev/mcp"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"worklore": {
"type": "http",
"url": "https://worklore.dev/mcp"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
ChatGPT solo se conecta a servidores en internet:
https://worklore.dev/mcpLos nombres de los menús pueden variar un poco según el plan y con el tiempo.
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Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Nombres y descripciones de las herramientas tal como los informó el servidor el 7 nov 2026. Los escribió el creador, no nosotros; los mostramos como texto sin formato.
check_capabilityDisclose what an agent Skill or worklore story CAN DO before you run it: a capability tier T0-T4 bound to a content sha256, with findings that carry file:line evidence, PLUS a separate list of behavioral red flags (prompt-injection / deception / exfiltration-intent / safety-bypas
get_storyFetch one worklore story by slug — its full markdown (narrative + the 'Reproduce this' contract your agent would run) WITH its capability disclosure attached (tier + findings), so you see what it can do before applying it. Read the capability first; run check_capability on the li
search_storiesSearch worklore stories by keyword across title, summary, tags and stack. Returns matches with their capability tier.
explore_keywordsThe worklore keyword map: every story tag with its story count, in four editorial groups (tools and agents, building blocks, practices, off the clock), plus the stories under one keyword when you name it. Use it when the user asks what worklore has on a topic, or wants to browse
suggest_for_projectGiven a short description of the current project (stack, what you're building, recent problems), suggest up to 3 worklore stories worth reproducing here, with why each fits and its tier.
report_reproductionCall this right after you apply a worklore story's steps to the user's own task, to record the reproduction (attributed to the signed-in account). Use an honest result: 'worked', 'partial' (you produced the output but it isn't verified yet), or 'failed' — all are useful. One coun
report_checkRecord the result of a story's read-only 'Check if this applies to you' section, run in the user's own project (attributed to the signed-in account). Run ONLY that check — change nothing, apply no fix. First decide whether it applies at all: if the project does not match the chec
publish_storyPublish a NEW worklore story as the signed-in account. worklore stories are PUBLIC and honest, so before you call this you MUST show the human the complete draft — the title, the first-person narrative, and the 'Reproduce this' contract — and get their EXPLICIT approval. Never pu
edit_storyRevise a worklore story the signed-in account PUBLISHED — only its author can edit it. Call get_story first, then show the human a before/after diff of your change and get their EXPLICIT approval before calling this; never edit on your own initiative. Send the COMPLETE revised st
suggest_editPropose a revision of a worklore story written by SOMEONE ELSE, for its author to accept or decline — worklore's pull request. Use it when, while reproducing a story, a step turned out wrong, outdated or missing (a library changed, the docs caught up, a command no longer exists).
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub worklore, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Respondió en 393 ms (HTTP 200)
No hace falta iniciar sesión
Leímos 10 descripciones de herramientas y no encontramos instrucciones ocultas para la IA
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 3 de 3 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.
El repo de GitHub cambió por última vez –, y la última versión (0.9.0) llegó al registro hace 11 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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 — all without an account — and, once you've signed in, record how a reproduction went, publish a story of your own, or revise one you published.
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 (public stories only; check_capability with a url needs sign-in, because the server fetches it for you):
| 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 |
report_check | slug, result (has_problem/no_problem), note *(optional)* | the recorded result of a story's read-only "Check if this applies to you" section, run in your project. Only for stories that have one (get_story says has_check: true). Never record "not applicable" — when your project does not match the check's preconditions, don't call it. One result per person per story; the latest replaces the earlier one |
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 |
edit_story | slug, markdown (the full revised story), kind (rephrase/addition/correction, default rephrase), note *(required for a correction)*, source *(optional https URL)* | the slug, URL, the recorded revision (at, kind, note, source) and how many reproducers were notified. Only the story's author can edit it. Show the author a before/after diff and get their approval first. The story's date never changes. If something in the story was wrong, it is a correction — which tells everyone who reproduced it — never a rephrase |
suggest_edit | slug, markdown (the complete story as you propose it), rationale (one or two lines: what was wrong or outdated, what you changed) | the suggestion id, its status (open), the story URL and a note. For a story by SOMEONE ELSE — worklore's pull request. Show the user the before/after diff and get their approval first. The story does not change: its author is notified and either accepts it as a credited revision or declines it, optionally handing the text back as a draft of the user's own. One open suggestion per person per story; sending another replaces it. For the user's own story use edit_story |
All eight carry MCP annotations (readOnlyHint / openWorldHint / idempotentHint) so a client can tell the user what a call will do before they approve it, and all eight 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.
Since 0.6.0 resources/list is a fixed list of three documents — the same for everyone, every day — all readable without an account:
| URI | What it is |
|---|---|
worklore://guide | How to use worklore through MCP: search, read a story with the user before acting, reproduce it, report honestly (failed is useful), x-ray unfamiliar skills and prompts with check_capability, publish or edit only with the user's approval |
worklore://story-format | The story format: frontmatter fields, the narrative, the "Reproduce this" contract (prerequisites / your agent will need from you / steps / verify), the optional read-only check, fail stories, proposals, sanitising, the exact-references rule. Read it before drafting a story |
worklore://access | What answers without a token and what needs sign-in — rendered from the one access table the server enforces |
Stories are reached through one resource template, worklore://story/{slug} (resources/templates/list). Public stories read without a token; a private story reads only for its author and answers like a missing one to everyone else. Every worklore://story/… URI that resources/list handed out before 0.6.0 still reads. To *find* a story, use search_stories / suggest_for_project.
Why the stories left the list: a list that changes whenever someone publishes cannot be part of a surface fingerprint — the fingerprint would "break" every day without anything breaking, and teach clients to ignore a mismatch. The contents of the three documents may change between releases; the list entries may not without a new version.
A version number is a promise that nothing a client depends on changed without it. Since 0.6.0 worklore publishes its surface fingerprint in the shared form `mcp-surface/1` (SPEC, by Sidney Bissoli), so you check worklore exactly the way you check every other server that publishes it. The registry entry carries it in server.json under _meta → io.modelcontextprotocol.registry/publisher-provided → io.github.sidneybissoli/mcp-surface:
declared.sha256 — the sha256 of what a client sees before it calls anything: the initialize result (protocol version, capabilities, instructions, serverInfo without its version) and the four lists (tools, resources, resource templates, prompts), normalised and serialised as the SPEC says;anonymous — which methods answer without a token (plus one named, harmless tools/call: check_capability on inline text), and its sha256.The fastest check is Sidney's dependency-free verify.mjs (Node 18+). It reads the registry entry for the version, makes sure the endpoint can say "no" to a method that does not exist, captures the live surface, and compares:
curl -sO https://raw.githubusercontent.com/SidneyBissoli/mcp-br-commons/main/packages/mcp-surface/exemplos/verify.mjs
node verify.mjs io.github.worklore/worklore 0.7.0
Or in Python, with nothing installed (the declared hash only):
python3 - <<'PY'
import hashlib, json, urllib.request EP = "https://worklore.dev/mcp" def rpc(method, params=None): body = {"jsonrpc": "2.0", "id": 1, "method": method, **({"params": params} if params else {})} req = urllib.request.Request(EP, data=json.dumps(body).encode(), headers={"Content-Type": "application/json", "Accept": "application/json, text/event-stream"}) return json.load(urllib.request.urlopen(req)).get("result") def canon(v): # SPEC §3: keys by UTF-16 code unit, no whitespace, JSON.stringify strings if isinstance(v, dict): return "{" + ",".join(json.dumps(k, ensure_ascii=False) + ":" + canon(v[k]) for k in sorted(v, key=lambda s: s.encode("utf-16-be"))) + "}" if isinstance(v, list): return "[" + ",".join(canon(x) for x in v) + "]" return json.dumps(v, ensure_ascii=False) def listed(method, key): # this server answers each list in one page res = rpc(method) return res.get(key) if isinstance(res, dict) else None def by(items, key): return None if items is None else sorted(items, key=lambda x: str(x.get(key)).encode("utf-16-be")) init = rpc("initialize", {"protocolVersion": "2025-06-18", "capabilities": {}, "clientInfo": {"name": "verify", "version": "1"}}) version = init"serverInfo" surface = {"initialize": {"protocolVersion": init.get("protocolVersion"), "capabilities": init.get("capabilities"), "instructions": init.get("instructions"), "serverInfo": {k: v for k, v in init["serverInfo"].items() if k != "version"}}, "tools": by(listed("tools/list", "tools"), "name"), "resources": by(listed("resources/list", "resources"), "uri"), "resourceTemplates": by(listed("resources/templates/list", "resourceTemplates"), "uriTemplate"), "prompts": by(listed("prompts/list", "prompts"), "name")} live = hashlib.sha256(canon(surface).encode()).hexdigest() entry = json.load(urllib.request.urlopen( "https://registry.modelcontextprotocol.io/v0.1/servers/io.github.worklore%2Fworklore/versions/" + version)) published = entry"server""io.modelcontextprotocol.registry/publisher-provided""declared" print("version", version, "| live", live[:12], "| registry", published[:12], "| match" if live == published else "| DIFFERS") PY
If the version is the same and the hash differs, the server changed without saying so. Tell me in an issue. 0.5.1 published worklore's own per-section hashes under a surface key; 0.6.0 replaced them with this one shared format. The idea of publishing the fingerprint with each release came from a comment by @_firelinks under Sidney Bissoli's Your MCP server changed. Its version didn't.
Since 0.5.0 one rule decides it, everywhere — the site, the REST API and this server alike. It lives as a single table in worklore's backend (access.py, rendered as docs/ACCESS.md); the summary below is generated from it.
The rule. Anyone can search and read all public stories without signing in — site, REST API and MCP alike. Private stories and every write (publish, edit, report a reproduction or a check, visibility, per-user d
Solo se muestra el principio; lee el resto en el repo