io.github.gregpunchPublished by GitHub account gregpunchv0.3.0Updated Nov 2, 2026
Live health of 65 agent APIs/MCPs plus a 15-min LLM leaderboard; recommend(task) picks a provider.
The publisher's own server: daily.dev
Read-only status service that tells an assistant which AI APIs and MCP servers are up, and recommends a healthy provider for a given task.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/io.github.gregpunch%2Fagent-daily/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Add this to your client's mcpServers config.
{
"mcpServers": {
"agent-daily": {
"type": "http",
"url": "https://agent-daily.agentdaily.workers.dev/mcp"
}
}
}A free, hourly reliability index for the APIs and MCP servers AI agents call: 65 providers across LLMs, search, scraping, email, vector DBs, voice, payments, messaging, maps, CRM, storage and public remote MCP servers, with 7-day uptime, p50/p95 latency and incident history.
Built for agent builders. Check before your agent calls a tool, fall back when a tool is down, and stop burning retries on outages.
list_tools, tool_statusFields: schema_version, generated_at (UTC), summary.{up,total}, and tools[] with name, category, up, http_status, latency_ms, vendor_status, uptime_24h_pct, checks_24h, error. Data is refreshed hourly; treat it as stale if older than about 2h. Please cache.
Limits: these are reachability checks only (an expected HTTP code), not correctness or quality tests. There is a single probe location.
A free public status page for 65 tools AI agents depend on. This is Phase 1, a two-week validation.
Files: tools.json (config), tools.md (list + method), check.py, build.py, site/ (static output), preview.png.
Recommended: GitHub Actions + GitHub Pages ($0).
.github/workflows/check.yml with schedule: cron: "0 * * * *" (hourly). Steps: checkout, pip install requests, python check.py && python build.py, commit results.db back (or store it as an artifact), then deploy site/ with actions/deploy-pages.Alternative: Cloudflare Worker cron + D1 + Pages ($0). Port check.py to a Worker scheduled() handler (free tier: 100k requests/day, cron triggers included). Store rows in D1 (free 5 GB), and render the page or serve JSON from the Worker or Pages. This option is the better base for the paid MCP/API later.
mcp-worker/)This is a stateless, read-only MCP server on a Cloudflare Worker. It uses Streamable HTTP at /mcp and offers two tools: list_tools(category?) and tool_status(name). Both read status.json with a 5-minute cache. It also serves /.well-known/mcp/server-card.json.
Remote endpoint: https://agent-daily.agentdaily.workers.dev/mcp (Streamable HTTP, no auth, read-only)
recommend(task): maps a phrase or category ("send email", "web search", "llm", "scrape a page") to a category and returns the healthiest provider plus 1-2 fallbacks, with reasons and freshness.incidents(name?, days=7): outages and vendor incidents with UTC start/end.list_tools(category?): matches either category or routing task.tool_status(name): full record, including 7-day uptime and p50/p95.Data: status.json (current + 7d stats) and history.json (incidents), both regenerated hourly.
llm_leaderboard(sort?) at https://agent-daily.agentdaily.workers.dev/mcphttps://gregpunch.github.io/agent-daily/llm/: every 15 minutes ~20 popular models (via OpenRouter, plus optional direct OpenAI/Anthropic/Gemini control checks) get "Reply with exactly the word pong". Leaderboard (score = 60% 24h correctness + 40% speed), per-model detail pages and a methods page. Data: llm/leaderboard.json, llm/models/<id>.json. MCP tool: llm_leaderboard(sort?). Probing skips cleanly when no keys are set; spend is capped at $2.50/30 days in llm/models.json.
Source: README.md at commit 200fac9
Live LLM leaderboard
Which LLMs are up, correct and fast right now. Every 15 minutes ~20 popular models (OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, xAI, Qwen, Cohere...) are asked to reply 'pong'; returns rank, score (60% 24h correctness + 40% speed), correct %, p50 time-to-first-token, p50 total time, cost per 1k calls, uptime and last result. Use to pick a fast, reliable model. sort: score (default) | correct | ttft | total | cost.
sortlimitRecommend a healthy provider for a task
Before calling an external API, ask which provider to use. Give a task phrase or category (e.g. 'send email', 'web search', 'llm', 'scrape a page', 'vector db', 'speech to text', 'payments', 'geocode'). Returns the top healthy pick plus 1-2 fallbacks ranked by live status, vendor status, 7-day uptime and latency, with a reason and data freshness.
taskrequiredRecent incidents
Outages (consecutive failed probes) and vendor status-page incidents with UTC start/end over the last N days (max 7). Optional provider name filter. Use to judge whether a failing API is a known incident.
daysnameList monitored tools
List the APIs and MCP servers Agent Daily monitors, with current up/down, latency and vendor status. Call before choosing a provider. Optional category filter (e.g. LLM, MCP, Search, Payments, Comms, Infra).
categoryGet one tool's status
Full status record for one monitored tool (up, http_status, latency_ms, vendor_status, uptime_24h_pct). Case-insensitive name or substring, e.g. 'openai', 'GitHub MCP'. Reachability only, not correctness.
namerequired90% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
Declare a license in the repository or the registry entry.
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claude mcp add --transport http agent-daily https://agent-daily.agentdaily.workers.dev/mcpimport requestss = requests.get("https://gregpunch.github.io/agent-daily/status.json", timeout=5).json()tool = next(t for t in s["tools"] if t["name"] == "OpenAI API")if not tool["up"] or tool["vendor_status"] in ("major", "critical"): ... # route to a fallback providerpython3 check.py # probe all tools -> results.db (SQLite)python3 build.py # render site/index.htmlcd mcp-worker && npm install && npx wrangler dev # localnpm test # MCP SDK client check against localhost:8787npx wrangler deploy # needs CLOUDFLARE_API_TOKEN + CLOUDFLARE_ACCOUNT_ID