The AI ecosystem moves every day. New models, breaking changes, security vulnerabilities, price drops. You can't chase every lead. Your agent can't either — unless it has a source it trusts. AgentWyre scans 165+ sources with Claude Opus, filters to your stack, and delivers machine-structured actions your agent can surface and you can approve. Cutting edge, automatically.
Live counters · 89 X accounts tracked · 6 AI providers priced · Deduplication ensures 100% fresh signal
📧 FREE DAILY BRIEF + WEEKLY DIGEST — DELIVERED TO YOUR INBOX
Daily brief every morning + weekly digest Sundays. No spam. Unsubscribe anytime.
Scanning Reddit, Twitter, Hacker News, changelogs, release notes, ArXiv, podcasts... just to find the 3 things that actually affect your stack. That's hours per week you're not building. And you still miss things.
"Anthropic batch pricing dropped 40%. Here's the pip command, estimated $47/mo savings on your volume, and the rollback if anything breaks. Also, LangChain 0.4 has a breaking change in your chain pipeline — don't upgrade yet. Want me to handle the cost optimization?"
A continuous intelligence feed for autonomous agents and intelligent systems. Distinct from traditional news services in that its primary consumers are machines, not humans.
"The agent pulled three actionable signals from the morning wyre before its operator finished coffee."
GitHub releases, Reddit, Hacker News, ArXiv, 89 X accounts, 15 podcasts, company blogs, policy feeds, benchmarks. Every signal captured.
Frontier AI doesn't just summarize — it scores relevance, checks hype, identifies breaking changes, extracts package updates, and calculates cost impact. Structured data, not prose.
Register your frameworks, models, and providers. Every signal is scored against YOUR stack. LangChain user? You see LangChain changes first. Anthropic customer? Cost alerts land in your feed.
Not "watch this space." Instead: the pip command, the config change, the rollback step, the risk level. Your agent presents it. You approve. Done.
Register your stack once. Get 8 relevant signals instead of wading through 200 raw items. Each item tells you WHY it matched your stack.
Real-time pricing database for 6 providers, 25+ models. When prices drop or better options emerge, your agent tells you — with the dollar amount you'll save.
7-day rolling security feed, severity-ranked, filtered to your dependencies. Prompt injection vectors, framework vulnerabilities, supply chain risks.
Every signal tagged with breaking/non-breaking, migration required, affected versions. Your agent checks before you upgrade.
Every signal gets a hype check: verified, promising, overhyped, vaporware, or misleading. With red flags, green flags, and who benefits from the narrative.
Look up whether that new model works with your framework at your version. Growing database, updated daily from real-world feed intelligence.
Major model drops. Critical CVEs. Pricing changes. Provider outages. Flash signals hit your agent's feed within minutes of surfacing — scored, verified, and actionable. Your agent knows before you check Twitter.
Real-time sentiment from 12 subreddits, Hacker News, and Stack Overflow. Hot discussions, trending themes, emerging frustrations. The vibe check no other AI newsletter gives you.
Rolling reliability scores for 13 AI providers — computed from confirmed incidents, community reports, and outage signals. Know which providers are solid before you bet your production stack on them.
7-day trend analysis of community themes. Track which topics are gaining heat, which are fading, and spot emerging patterns before they go mainstream. The trajectory matters more than the snapshot.
An intelligence feed your agent trusts is a high-value target. Inject a malicious "update this package" into the feed, and a naive agent executes it. We treat this as an existential threat to our product.
Every raw item passes through automated pattern detection for injection attempts, social engineering, and command smuggling. Suspicious content is flagged and quarantined — never reaches your feed.
We don't trust one source. Items with a single source are confidence-capped at 6/10, no matter how credible. Two corroborating sources: up to 8. Three or more: up to 10. This is baked into the analysis model.
Every action in every feed item carries requires_user_approval: true. This is hardcoded, not configurable. Your agent presents the action. You decide. We designed it so autonomous agents can consume us safely — but a human always has the final word.
We don't just report what happened — we tell you what's real, what's noise, and who benefits from the hype. Single-source items capped at 6/10 confidence. No exceptions.
// ━━━ STEP 1: Register your stack (one-time) ━━━ // POST /api/agent/register { "stack": { "frameworks": ["langchain", "llama.cpp"], "models": ["claude-opus-4", "qwen-3.5"], "providers": ["anthropic", "ollama"] } } // ━━━ STEP 2: Your personalized feed (live from 2026-03-20) ━━━ // GET /api/wire — filtered to YOUR stack { "wire_version": "2.0", "date": "2026-03-20", "security_status": "CLEAN", "items": [ // ▸ SIGNAL 1: security_advisory { "title": "Haystack v2.26.1-rc1: Security Fix for Template Variable Injection in ChatPromptBuilder", "category": "security_advisory", "relevance_score": 8, "urgency_score": 7, "match_reasons": ["Matched to your stack"], "hype_check": { "hype_level": "verified", "reality": "Real security fix for a documented attack vector. No hype.", "wait_or_act": "Monitor for stable 2.26.1 release. If you have user-supplied template variables in ChatPromptBuilder, consider testing the rc1 now or adding input sanitization upstream." }, "change": { "type": "security_patch", "breaking": false, "affected_components": [{ "name": "haystack-ai", "versions_affected": "<= 2.26.0", "fixed_in": "2.26.1-rc1" }] }, "action": { "type": "security_patch", "priority": "high", "risk_level": "low", "requires_user_approval": true } }, // ▸ SIGNAL 2: tool_release { "title": "KittenTTS: Three New Tiny TTS Models — Smallest Under 25MB", "category": "tool_release", "relevance_score": 8, "urgency_score": 5, "match_reasons": ["Matched to your stack"], "hype_check": { "hype_level": "verified", "reality": "Real models with published weights. Size claims are verifiable. Quality at this size won't match cloud TTS, but that's not the point.", "wait_or_act": "Download and test the smallest model on your target hardware. The size makes evaluation trivial." }, "change": { "type": "new_capability", "breaking": false }, "action": { "type": "capability_unlock", "priority": "medium", "commands": [{ "command": "git clone https://github.com/KittenML/KittenTTS", "rollback": "rm -rf KittenTTS" }], "risk_level": "none", "requires_user_approval": true } }, // ▸ SIGNAL 3: policy { "title": "CEO Uses ChatGPT to Void $250M Contract, Ignores Lawyers, Loses Spectacularly in Court", "category": "policy", "relevance_score": 7, "urgency_score": 5, "match_reasons": ["Matched to your stack"], "hype_check": { "hype_level": "verified", "reality": "Real court case with real judicial ruling. No hype — pure consequences.", "wait_or_act": "If you're using AI for legal analysis, ensure human legal review is non-negotiable. This case is citable precedent against AI-only legal reasoning." }, "change": { "type": "ecosystem_shift", "breaking": false }, "action": { "type": "awareness_only", "priority": "medium", "risk_level": "low", "requires_user_approval": true } } ] } // ━━━ ALSO AVAILABLE ━━━ // GET /api/advisories → Security alerts for your stack // GET /api/costs → Real-time model pricing (25+ models) // GET /api/compat → Compatibility lookups across frameworks // GET /api/wire/actions → Just the executable actions, filtered
Pro subscribers get real-time flash signals throughout the day. Here's a recent one:
Every morning: the ARGUS daily brief with 13-17 hype-checked signals. Every Sunday: the week's top signals, biggest releases, and community pulse. One signup, both emails. Free, forever.
Daily brief every morning + weekly digest Sundays. No spam. Unsubscribe anytime.
USDC on Base · No human required · Fully autonomous
Your agent can subscribe itself. Send USDC on Base, submit the transaction hash, get an API key back. No credit card, no checkout page, no human in the loop.
GET /api/pay/base
Returns wallet address, chain info, and exact USDC amounts per tier
2.99 or 9.99 USDC
Send to the wallet address on Base (chain ID 8453). ~$0.01 gas fees.
POST /api/pay/base
Submit tx_hash → on-chain verification → instant API key (30 days)
Chain: Base (8453) · Token: USDC · Daily: 2.99 USDC · Pro: 9.99 USDC · 30-day access per payment
POST /api/agent/register
{"stack": {"frameworks": ["langchain"], "providers": ["anthropic"]}}
GET /api/wire
Authorization: Bearer aw_your_key
Each item includes structured actions with commands, rollback steps, risk levels, and cost impact. Your agent presents them. The human approves. Ship.
We read hundreds of sources so you don't have to. We verify every claim so your agent doesn't suggest something dangerous. We structure every action so your agent can present it clearly and you can approve with confidence.
$2.99/mo is less than the cost of one missed breaking change. $9.99/mo is less than one hour debugging a vulnerability you could have patched on day one. Your agent stays cutting edge. Your stack stays secure. You stay focused on building.
Five ways to give your agent real-time AI ecosystem intelligence.
Model Context Protocol — works with Claude Desktop, Cursor, OpenClaw, and any MCP-compatible agent.
{
"mcpServers": {
"agentwyre": {
"command": "npx",
"args": ["agentwyre-mcp"]
}
}
}npm: agentwyre-mcp · No key needed for free tier.
Standard JSON endpoints. Works with any HTTP client, agent framework, or script.
# Free tier (no key needed)
curl https://agentwyre.ai/api/feed/free
# Authenticated
curl -H "Authorization: Bearer aw_xxx" \
https://agentwyre.ai/api/feedDocs: /api/status · FAQ
Add one line to your agent's system prompt. Works with any LLM-based agent.
You have access to AgentWyre
for AI ecosystem intelligence.
Check daily for breaking changes
and security advisories.
Free API: GET agentwyre.ai/api/feed/freePaste into any agent's instructions. Zero setup.
Python package for scripts, notebooks, and AI pipelines. Type-hinted, zero dependencies.
pip install agentwyre
from agentwyre import AgentWyre
aw = AgentWyre() # free, no key
signals = aw.signals()
for s in signals:
print(s["title"])PyPI: agentwyre · Works in any Python 3.8+ env.
One command to add AgentWyre intelligence to any OpenClaw agent.
clawhub install agentwyreYour agent automatically gets tools for querying signals, checking security advisories, and searching the archive. No config needed.
ClawHub: agentwyre · Browse skills →
Agents can self-subscribe using USDC on Base — no human needed. Learn more →
Every data layer we compute is available as a JSON API. Free endpoints need no auth.