AWS Agentic AI
zxkane/aws-skills
AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale.
Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is…
$ npx skills add gotempsh/temps --skill temps-mcp-setup -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gotempsh/temps temps-mcp-setup --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gotempsh/temps.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/temps-mcp-setup .claude/skills/temps-mcp-setup && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "temps-mcp-setup" agent skill from https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setup into .claude/skills/temps-mcp-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "temps-mcp-setup", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setupType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gotempsh/temps --skill temps-mcp-setup -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gotempsh/temps temps-mcp-setup --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotempsh/temps.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/temps-mcp-setup .agents/skills/temps-mcp-setup && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "temps-mcp-setup" agent skill from https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setup into .agents/skills/temps-mcp-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "temps-mcp-setup", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gotempsh/temps --skill temps-mcp-setup -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gotempsh/temps temps-mcp-setup --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotempsh/temps.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/temps-mcp-setup .cursor/skills/temps-mcp-setup && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "temps-mcp-setup" agent skill from https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setup into .cursor/skills/temps-mcp-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "temps-mcp-setup", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gotempsh/temps.git --path skills/temps-mcp-setup--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gotempsh/temps --skill temps-mcp-setup -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gotempsh/temps temps-mcp-setup --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotempsh/temps.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/temps-mcp-setup .gemini/skills/temps-mcp-setup && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "temps-mcp-setup" agent skill from https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setup into .gemini/skills/temps-mcp-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "temps-mcp-setup", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gotempsh/temps temps-mcp-setupInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gotempsh/temps --skill temps-mcp-setup -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gotempsh/temps.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/temps-mcp-setup .github/skills/temps-mcp-setup && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "temps-mcp-setup" agent skill from https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setup into .github/skills/temps-mcp-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "temps-mcp-setup", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gotempsh/temps --skill temps-mcp-setup -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gotempsh/temps temps-mcp-setup --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gotempsh/temps.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/temps-mcp-setup .opencode/skills/temps-mcp-setup && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "temps-mcp-setup" agent skill from https://github.com/gotempsh/temps/tree/main/skills/temps-mcp-setup into .opencode/skills/temps-mcp-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "temps-mcp-setup", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
temps-mcp-setupConfigure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is…
Temps MCP Setup is an agent skill from gotempsh/temps. Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is enabled) triggering deployments with human confirmation. Use when the user wants to: (1) Set up the Temps MCP server, (2) Connect Claude Code/Desktop, Codex, Cursor, VS Code, Windsurf, or Zed to Temps, (3) Add Temps tools to an AI assistant, (4) Test the MCP wizard locally, (5) Manage multiple Temps MCP connections (dev…
Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering MCP servers and Deployment. It works with Model Context Protocol and Visual Studio Code. The repository describes itself as: AI-native open-source alternative to Vercel + Sentry + PostHog + Pingdom + Resend + E2B. 440+ CLI operations with drop-in skills for Claude Code, Codex & OpenCode — deployments… The licence is Apache-2.0.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 5e7963a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
bunxcurlclaudecodexFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use bunx and curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Temps MCP Setup loads about 3.7k tokens when it runs. Until then it costs about 183 tokens; SKILL.md has 1,771 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from gotempsh/temps at commit 5e7963a, republished under its Apache-2.0 licence (© gotempsh). 1,771 words, ~3,651 tokens.
.claude/skills/temps-mcp-setup/SKILL.md (or your agent's skills folder).Temps serves MCP (Model Context Protocol) directly from the temps binary itself
(ADR-039, crates/temps-mcp-server) -- there is no separate package to install or
keep up to date. The MCP endpoint calls the same service layer as the REST API, so
it cannot drift from it the way the old standalone @temps-sdk/mcp npm package did
(removed in PR #355 for exactly that reason -- do not reinstall it or point a
client at it).
Installer wizard lives in apps/temps-cli/src/commands/mcp/
(bunx @temps-sdk/cli mcp add|remove|status).
Off by default (AppSettings.mcp_server.enabled = false), so a fresh install never
exposes it unconfigured. Turn it on as an admin:
bunx @temps-sdk/cli mcp enableIf you're not logged in yet, mcp enable offers to run the device-flow login
inline (see Auth model, precisely
below) -- no separate temps login step required first.
mcp enable does the same GET-modify-PUT round-trip against /api/settings the
handler requires (it takes the full AppSettings object, not a partial patch),
merging onto whatever is already fetched so it can never clobber another admin's
settings. mcp disable reverses it.
Verify it took effect, or check status any time without re-running enable:
bunx @temps-sdk/cli mcp status
# "This instance: <check> enabled (http://localhost:8080)" or "<bullet> disabled (...)"Or probe the endpoint directly (no auth needed for this one):
curl -s http://localhost:8080/mcp/tools
# {"groups":[{"key":"deployments","label":"Deployments & Projects"}, ...]}
# A 404 here means the flag is still off (or this instance predates MCP support).bunx @temps-sdk/cli mcp add <client><client> is one of: claude-code, claude-desktop, codex, cursor, vscode,
windsurf, zed.
Auth model, precisely: mcp add/mcp enable/mcp disable need you logged
into the CLI so the wizard can mint an API key on your behalf -- that login has
nothing to do with MCP itself. If you're not already logged in, these commands
detect that and offer to run the device-authorization flow right there (prompts
"Log in now?", then "Temps server URL", defaulting to your current config) rather
than erroring out and making you run temps login as a separate step first. Under
the hood it's the same flow temps login uses (/auth/cli/device/start +
/auth/cli/device/poll, server-authoritative polling, no code to type, browser
approval). In --yes (non-interactive) mode this inline offer is skipped --
pass --api-key or ensure a context is already logged in. What actually gets
written into the AI client's config either way is a plain, long-lived
Authorization: Bearer <api-key> header -- the same static-bearer-token pattern
PostHog's own MCP wizard uses, and one of the two auth patterns the MCP HTTP
transport spec supports (the other being full OAuth 2.1 + dynamic client
registration, which most of these 7 clients don't yet implement for remote MCP
servers anyway).
The wizard will:
/mcp/tools to confirm the instance has MCP enabled (see step 1). If it
404s, it tells you so and stops -- it will not silently write a broken config.role_type: 'reader' when write mode is off, 'user' when it's on (the user role
carries DeploymentsWrite; reader does not).claude mcp add / codex mcp add so their config format is never
hand-maintained here).Other subcommands:
bunx @temps-sdk/cli mcp status # which clients on this machine have Temps configured
bunx @temps-sdk/cli mcp remove <client>Restart the AI client after running mcp add -- most clients only read MCP config
at startup.
Bring up a local instance with the start-temps skill first (or reuse one you
already have running), noting its slot -- every non-zero slot has its own
ports, database, and login, so treat the printed web/api URLs as this
instance's identity for the rest of this section.
Fastest path to a working test without the interactive prompts: mcp add --yes
with an explicit --api-key, pointed at the slot's API URL via TEMPS_API_URL (or
--target-context, if you've already run temps login against that instance and
saved a context).
# One-time per slot: enable the flag (step 1) and mint a throwaway admin key
# (or use the wizard's own key-creation step interactively instead).
TEMPS_API_URL=http://localhost:<8080+slot*10> bunx @temps-sdk/cli mcp add claude-code \
--api-key <key> --yesThen drive the protocol directly with curl -- this is the fastest way to verify
the server side without depending on any particular AI client being installed:
API=http://localhost:<8080+slot*10>
KEY=<your-api-key>
# Capability probe (no auth)
curl -s "$API/mcp/tools"
# initialize
curl -s "$API/mcp" -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'
# tools/list -- add ?write=1 to the $API/mcp URL to also see trigger_deployment/confirm_action
curl -s "$API/mcp" -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}'
# tools/call
curl -s "$API/mcp" -H "Authorization: Bearer $KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"list_projects","arguments":{}}}'If list_projects returns [], there's nothing to look at yet -- create a project
via the normal REST API or the web UI first (create_project is not an MCP tool;
see Current Coverage below).
Testing the write flow (propose-then-confirm): call trigger_deployment on the
?write=1 connection with a real project_id/environment_id, note the
_proposal_token in the response, then call confirm_action with that token
within 5 minutes. Confirm it only works once -- replaying the same token must
return a Proposal token not found or already used error. If you have DB access,
confirm the audit row landed: SELECT * FROM audit_logs WHERE operation_type = 'MCP_DEPLOYMENT_TRIGGERED' ORDER BY id DESC LIMIT 1;.
Testing an actual AI client end-to-end: after mcp add <client> and a restart,
ask it something that requires a tool call ("list my Temps projects") and confirm
it actually invokes list_projects rather than hallucinating an answer -- most
clients show a tool-call approval prompt or a visible "using tool" indicator you
can check against the request actually hitting your instance's logs.
You will commonly have more than one Temps instance you want an AI client talking to at once -- several local dev slots, or dev + staging + prod. Each is a fully independent MCP connection: a distinct URL, a distinct API key, and (for clients that support named servers) a distinct entry in that client's config.
mcp add <client> once per instance you want configured. The wizard
does not currently namespace by instance -- it writes to the single temps
entry key most clients use (mcpServers.temps / context_servers.temps /
etc.), so adding a second instance for the same client overwrites the
first entry rather than adding a second one. If you need two Temps connections
live in the same client simultaneously today, hand-edit the client's config
file after running the wizard once, duplicating the temps entry under a
second key (e.g. temps-staging) with that instance's URL/key -- the wizard
itself doesn't offer this yet.bunx @temps-sdk/cli mcp status only reports whether a Temps entry exists
per client, not which instance it points at -- check the URL inside the config
file directly if you've hand-edited it, or bunx @temps-sdk/cli mcp remove <client> and re-run mcp add when switching which instance a client talks to.mcp add run against a
different instance should mint its own key on that instance (step 2.4) rather
than reusing one key across instances -- keys don't work cross-instance anyway
(each instance has its own user/key table), but it also keeps revocation
scoped: pulling a compromised or no-longer-needed key from one instance's
Settings -> API Keys doesn't touch the others.start-temps slot
is already a fully separate instance (own port, own DB, own admin login) --
point TEMPS_API_URL at the specific slot you're testing (see the start-temps
skill for the port formula) and mint a key on that slot. Don't reuse a key
minted on slot 0 against slot 3's API URL; it will 401 (different DB, different
users table).mcp add runs (two keys, two config entries) rather than one -- the
wizard's write-mode question is per-connection, not a runtime toggle.Tools are organized into 7 groups, selectable via the wizard or the connection
URL's ?groups= param:
| Group | Contents |
|---|---|
deployments | projects, deployments, environments, presets |
infrastructure | services, containers, load-balancer, scans |
networking | domains, custom-domains, dns-providers, ip-access |
data | backups, dsn |
observability | monitors, incidents, errors, proxy-logs, funnels, analytics |
notifications | notifications, notification-prefs, webhooks, email-domains, email-providers |
platform | users, settings, api-keys, audit, tokens, platform |
Current coverage: only platform (list_projects, get_project) and
deployments (list_deployments, and the write tools trigger_deployment /
confirm_action) have real tools implemented so far. The other five groups exist
in the taxonomy but have no tools registered yet -- tools/list omits them until
they're ported from the old mcp/src/tools/*.ts reference implementations (kept
on this branch for reference, not published). Notably, there is no
create_project MCP tool yet -- create projects via the REST API or web UI, then
use MCP to list/inspect/deploy them.
When a client is configured with write mode on, calling a write tool (e.g.
trigger_deployment) does not execute immediately. It returns a proposal
describing the intended action and a short-lived (5 minute), single-use token. The
AI client shows this to you; if you approve, it calls confirm_action with that
token, which is the only path that actually executes the mutation. Declining, or
letting the token expire, does nothing. Every successful confirm_action write is
audit-logged (MCP_DEPLOYMENT_TRIGGERED) with the calling user, IP, and user
agent, same as the equivalent REST endpoint.
This means enabling write mode does not hand an AI assistant unsupervised control of your infrastructure -- every mutation still needs an explicit confirmation step in the conversation.
Every request except GET /mcp/tools requires Authorization: Bearer <api-key>,
validated by the same auth path as the REST API. A key's existing scoped
permissions apply normally -- an MCP tool that needs DeploymentsWrite is
rejected exactly like the equivalent REST call would be if the key lacks it.
?groups= / ?write=1 only narrow what a call could reach; they never grant
permissions the key doesn't already have.
mcp add reports "this instance does not support MCP":
TEMPS_API_URL (check bunx @temps-sdk/cli status).Tools not appearing in the AI client after mcp add:
bunx @temps-sdk/cli mcp status to confirm the config was actually written.claude mcp list / codex mcp list directly to check
their own registry.Write tool calls fail with a permission error even though write mode is on:
?write=1 only controls whether write tools are listed; the API key still
needs the underlying permission (e.g. DeploymentsWrite) to actually call one
-- that check happens at call time, the same as the equivalent REST endpoint.A tool call returns "unknown tool":
?groups= in the config
URL) -- a tool outside the active groups is not registered at all, not just
hidden.Local testing hits a "preview gateway: forbidden" error instead of your MCP
response: unrelated to MCP -- the global temps-preview-gateway Docker
container's host port mapping can coincidentally collide with a dev slot's HTTP
port. Hit the machine's real LAN IP (ifconfig, not localhost/127.0.0.1)
instead; the temps serve process binds 0.0.0.0, so it's reachable on any
interface even when 127.0.0.1:<port> is claimed by the gateway container.
© gotempsh, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/temps-mcp-setup of gotempsh/temps.
Open the folder on GitHubat commit 5e7963a
Temps MCP Setup next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Temps MCP Setup this skillgotempsh/temps | 826 | — | ~3.7k | Automated safety check: Pass | Apache-2.0 | |
| AWS Agentic AIzxkane/aws-skills | 367 | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Claude Docs Consultantcentminmod/my-claude-code-setup | 2.7k | — | ~959 | Automated safety check: Pass | MIT | |
| Olore Claude Code Latestolorehq/olore | 104 | — | ~901 | Automated safety check: Pass | MIT | |
| Chatgpt AppsLeoYeAI/openclaw-master-skills | 2.2k | — | ~4.6k | Automated safety check: Pass | MIT | |
| FastmcpTommy-yw/RunbookHermes | 546 | 4 repos | ~2.1k | Automated safety check: Pass | MIT |
zxkane/aws-skills
AWS Bedrock AgentCore comprehensive expert for deploying and managing AI agents at scale.
centminmod/my-claude-code-setup
Consult official Claude Code documentation from code.claude.com using selective fetching.
olorehq/olore
Local claude-code documentation reference (latest). An agent skill from olorehq/olore.
LeoYeAI/openclaw-master-skills
Complete ChatGPT Apps builder - Create, design, implement, test, and deploy ChatGPT Apps with MCP servers, widgets, auth, database integration, and automated deployment
Tommy-yw/RunbookHermes
Build, test, inspect, install, and deploy MCP servers with FastMCP in Python.
awslabs/cli-agent-orchestrator
Enable, operate, and extend CAO's MCP Apps surface — the host-rendered fleet dashboard visible inside MCP App hosts (Claude Desktop, ChatGPT, VS Code Copilot, Goose, Postman).
gotempsh/temps
Manage, deploy, operate, and instrument applications with Temps.
gotempsh/temps
Add Temps analytics to React applications with comprehensive tracking capabilities including page views, custom events, scroll tracking, engagement monitoring, session recording, and Web Vitals…
gotempsh/temps
Best-practices reference for preparing and instrumenting applications on Temps.
gotempsh/temps
Operate Temps through the pinned @temps-sdk/cli package with bunx or npx.
gotempsh/temps
Design, build, test, and distribute external Temps plugins with TypeScript/Bun; provide development and local-testing guidance for existing Rust plugins.
gotempsh/temps
Add a custom domain to a Temps project and provision an automatic SSL/TLS certificate via Let's Encrypt, driven entirely from the @temps-sdk/cli CLI.
Works with
Categories
Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is…. Temps MCP Setup is an agent skill from gotempsh/temps. Configure Temps as an MCP (Model Context Protocol) server so AI assistants can interact with a Temps instance directly -- listing/inspecting projects and deployments, and (when write mode is enabled) triggering deployments with human confirmation.
Temps MCP Setup fits situations like: the user wants to:; set up the Temps MCP server; connect Claude Code/Desktop; add Temps tools to an AI assistant.
Run `npx skills add gotempsh/temps --skill temps-mcp-setup -a claude-code`. Or copy the skill folder (skills/temps-mcp-setup in gotempsh/temps) into .claude/skills/temps-mcp-setup in your project. Claude Code loads it when a task matches its description.
Run `npx skills add gotempsh/temps --skill temps-mcp-setup -a codex`. Or copy the skill folder (skills/temps-mcp-setup in gotempsh/temps) into .agents/skills/temps-mcp-setup in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gotempsh/temps --skill temps-mcp-setup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/temps-mcp-setup, .gemini/skills/temps-mcp-setup, .github/skills/temps-mcp-setup and .opencode/skills/temps-mcp-setup in your project.
Going by SKILL.md and its folder, Temps MCP Setup needs the command-line tools its instructions call (bunx, curl, claude and codex).
SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Temps MCP Setup is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Temps MCP Setup: AWS Agentic AI (zxkane/aws-skills, 367 stars), Claude Docs Consultant (centminmod/my-claude-code-setup, 2.7k stars), Olore Claude Code Latest (olorehq/olore, 104 stars) and Chatgpt Apps (LeoYeAI/openclaw-master-skills, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
gotempsh (a GitHub organization) maintains it in gotempsh/temps, which has 826 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 7, 2026.
Source: gotempsh/temps on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.