it’s been over a month since i graduated! 💙🌊 i wanted to let everyone know im doing okay and have taken a lot of time to pursue getting help for my health & am seeing some really good doctors this month! I’ve been very sick but ive been drawing a lot and started acupuncture treatments which i like! also yesterday i went on a walk in the sun!! it was so nice, i can’t wait for spring time. I hope you’re all doing good and i am secretly cheering on and supporting all my moots! i miss everyone so much!! 💙 :) keep on swimming and doing ur best!! much lub always!!

We built something that nobody else in this space has even attempted. Let me walk you through everything inside MPP32. The problem is simple. AI agents can call functions. But the second that function costs money, everything breaks. You need accounts at every provider. API keys for each one. Custom billing code. Budget tracking. Payment handlers. For every single service your agent touches. We killed all of that. MPP32 is a universal payment proxy for AI agents. One MCP server install. One line in your config. Your agent now has access to over 4,500 machine payable APIs across every category you can think of. Token intelligence. Market data. Web search. Image generation. DeFi analytics. Wallet scoring. Trading signals. On chain queries. All of it. Here is what makes this different from anything else out there. FIVE payment protocols. Not one. Five. x402 on Solana. x402 on Base. Tempo on Ethereum L2. ACP checkout sessions. AP2 with W3C Verifiable Credentials. AGTP with agent identity certificates. Your agent picks whichever one matches the keys you have configured. You write zero protocol code. The payment flow is dead simple. Agent requests a service. Gets a 402 challenge back. Our MCP server detects which protocol to use, signs the transaction LOCALLY on your machine, retries with proof, and returns the data. Your keys never leave your device. MPP32 never touches the money. Settlement goes directly from your wallet to the provider wallet. On chain. Verified. Auditable forever on Solscan or Basescan. We built an escrow pattern into x402 that nobody else has. The payment signature gets verified immediately but settlement only happens AFTER the upstream service returns a valid response. If the service fails or returns garbage, you do not get charged. Period. No other payment proxy does this. Now the Intelligence Oracle. This is our native Solana token analysis engine pulling from DexScreener, Jupiter, and CoinGecko simultaneously. For eight tenths of a penny per query you get an Alpha Score from 0 to 100, a Rug Risk rating on a 10 point scale, smart money signals including volume spikes and buy pressure and whale accumulation patterns, a 24 hour pump probability percentage, projected ROI ranges, whale activity levels with recent buy and sell counts, full market data including price changes across 1h 24h and 7d windows, volume, liquidity, market cap, FDV, pair age, DEX ID, and Twitter followers. All merged. All real time. All paid automatically through the protocol your agent already has configured. For M32 token holders we built three exclusive APIs that nobody else can access. Hold 1 million M32 and you unlock the Whale Tracker. Top 20 holder analysis. Concentration risk scoring. Buy and sell pressure tracking across 5 minute, 1 hour, 6 hour, and 24 hour windows. Volume spike detection. Whale accumulation versus distribution signals. Composite whale score from 0 to 100. Free for qualifying holders. Hold 2.5 million M32 and you unlock Token Comparison. Head to head intelligence on any two tokens. Alpha scores face off. Rug risk comparison. Volume and liquidity matchup. Pump probability side by side. Buy pressure comparison. Returns a winner verdict with full score breakdown. Also free. Hold 5 million M32 and you unlock the Portfolio Scanner. Point it at any Solana wallet. It automatically detects all SPL tokens, excludes stablecoins, runs full intelligence analysis on the top 10 holdings, aggregates portfolio risk, estimates total value in USD, identifies highest risk and best alpha tokens, scores diversification from 1 to 10, and breaks down holder concentration and buy sell pressure per token. Free. Discount tiers for everyone else. 250K M32 gets you 20% off every query. 1 million M32 gets you 40% off. Once we ship SIWS verification these activate automatically based on your on chain balance. No subscriptions. No accounts. Just hold the token. For API providers this is where it gets wild. Register your service at Fill out the form. Get approved instantly. Start receiving payments directly to your wallet within minutes. The fee we take? Zero percent. Providers keep 100% of revenue. Settlement is direct wallet to wallet. No batching. No minimum thresholds. No monthly payouts. x402 on Solana confirms in roughly 10 seconds. You see the money in your wallet before you finish reading this sentence. Register once and you automatically accept all five payment protocols. You do not need to implement Tempo. You do not need to implement ACP. You do not need to understand AP2 or AGTP. MPP32 handles all verification and settlement for every protocol. You just run your API. Every provider gets a full analytics dashboard. Real time query counts. Requests broken down by 24 hours, 7 days, and all time. Success rate. Average latency. Error counts. Estimated revenue. Per protocol usage metrics. Health monitoring with automatic endpoint checks. Three consecutive failures suspend your listing. Come back online and it auto recovers. Your listing gets published to our federated catalog of 4,500+ services. It gets added to our OpenAPI 3.1 spec that regenerates dynamically. It shows up in our A2A agent card at .well known/agent.json for agent to agent discovery. It appears in our MCP configuration endpoint. Every agent using MPP32 can now find and pay for your service without ever visiting your website. The catalog itself pulls from four sources. Native services registered through us. Curated free APIs like DexScreener and Jupiter and CoinGecko. The x402 Bazaar from Coinbase. And the official Model Context Protocol registry. All searchable. All filterable by category, protocol, source, network, chain, health status, price range, and verification status. Over 50 categories spanning AI inference, image generation, translation, embeddings, web search, news feeds, financial data, crypto analytics, DeFi, NFT intelligence, wallet scoring, OCR, document parsing, identity verification, fraud detection, code intelligence, security scanning, and dozens more. Budget controls are built into the infrastructure. Set a total session cap. Set an hourly velocity limit. Set an alert threshold. If your agent hits the limit a circuit breaker trips automatically and blocks all further spending. You get a clear error with the reason and a remedy. Reset manually when you are ready. Update budgets on the fly. If you raise the limit past current spend the breaker auto resets. Full spending analytics per service and per protocol available through the API. Security is not an afterthought. SSRF protection blocks requests to all private IP ranges, loopback addresses, link local addresses, IPv6 unique local, and cloud metadata endpoints. Applied on provider registration AND on every single proxy request because DNS can drift. All API keys hashed at rest with SHA256. Database leak does not expose live credentials. Management tokens for providers also hashed. Recovery OTPs hashed before storage with 15 minute expiry. Rate limiting on every admin endpoint. Zod schema validation on all inputs. Body size limits at 1MB. Path traversal prevention. URL validation. The server refuses to boot in production if signing secrets are missing or match known defaults. Idempotency is built in from day one. Every paid request gets an automatic idempotency key. LRU bounded cache at 5,000 entries with 10 minute TTL. Network retries cannot cause duplicate charges. Bounded memory so it does not bloat. The MCP server ships with eight tools. list_mpp32_services for browsing the catalog. call_mpp32_endpoint for calling any service with automatic payment. get_solana_token_intelligence for the oracle. get_m32_whale_tracker and compare_tokens_m32 and scan_portfolio_m32 for token gated premium features. manage_agent_budget for circuit breaker and spending controls. get_mpp32_diagnostics for troubleshooting. Works with Claude Desktop. Claude Code. Cursor. Windsurf. One npm install and you are live. We also ship a TypeScript SDK on npm. Import MPP32, pass your Solana key, call analyze() or listServices() or callService(). Automatic 402 handling. Automatic protocol detection. Automatic retry with exponential backoff. Configurable timeouts. Custom headers. Works in any Node.js environment. Agent sessions last 30 days. Full transaction logs showing every call with the service name, protocol used, price quoted, discount applied, price settled, settlement transaction signature, latency, and success status. Per protocol breakdowns with request counts, settled volume, and average latency for each of the five protocols independently. On chain verification means every single dollar that moves through this system is permanently recorded on the blockchain. Solana transactions on Solscan. Base transactions on Basescan. Immutable. Auditable by anyone. We are not asking you to trust us. We are asking you to verify. No subscriptions. No monthly fees. No account fees. No API key fees. No discovery fees. No settlement fees. No early termination fees. No minimums. You pay for what you use, the provider gets paid instantly, and the blockchain proves it happened. This is MPP32. The payment layer for autonomous AI agents. 4,500+ services. Five protocols. Zero platform fee. Instant on chain settlement. Token gated premium intelligence. Infrastructure grade budget controls. And we are just getting started. Ive put everything into this project and will continue to do so no matter what happens with the chart.. The full scale agent economy isn't even here yet. solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump

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anybody who uses or learns agentic systems, SHOULD READ THIS the install order I run before any new agentic project: 1. PRIVACY: direnv + a real secrets manager install direnv, then plug it into your team's password manager (1Password CLI via op run, doppler, infisical, vault, pick one) what direnv does: loads per-folder environment variables when you cd in, unloads when you cd out. the real move is wiring it into your secrets manager so credentials NEVER live in plain text on disk what this stops: - API keys accidentally committed to git history, the most common AI agent breach pattern in 2026 - credentials leaking from one project into another through your shell history - shared .env files that one teammate quietly backs up to Dropbox - secrets that survive a laptop theft because they were sitting in /Users/you/projects the part nobody mentions: most "my agent got jailbroken" stories actually trace back to one credential the agent had access to that it shouldn't have. scope keys to projects, scope projects to folders, and the blast radius of any single compromise drops dramatically I shipped 2 agents with keys in .env files before switching. the day I plugged direnv into op run I stopped having that whole class of nightmare 2. TOKENS: litellm or portkey as your model proxy one URL that fronts every AI provider (Anthropic, OpenAI, Google, Mistral, local models). all your spend flows through one place what it saves you: - response caching keyed by prompt hash, cuts your bill 30-60% on repeat tasks - automatic fallback on rate limits (Sonnet hits a 429? falls to Opus, then GPT, then your local backup, no broken users) - per-feature and per-user budget caps, block the call before it costs $200 instead of auditing it after - model routing rules, cheap tasks to Haiku, expensive ones to Opus, never the wrong way - PII redaction before requests leave your network, security side benefit the part nobody mentions: every "$4k AI bill" story I've heard ends with "we didn't have a proxy in front." this is where you put guardrails around spend BEFORE the spend happens I built my own router for 2 weeks. it took 20 minutes to replace with litellm. I will be embarrassed about this forever 3. CONTEXT: uv + git commit on every passing eval install uv (the new Python package manager, 10-100x faster than pip+venv, by the Astral team behind ruff). then commit every time an eval suite PASSES, with the model version and pass rate in the commit message what this preserves: - exact dependency set via uv.lock, you always know which packages your agent was using, no nasty surprises from a quiet update - exact prompt + code state, you can reproduce any past run from a single git hash - exact model version paired to exact pass rate, a paper trail when prod breaks weeks later - one-command rollback to a known-working state when a refactor goes sideways - a compliance story, every prompt version tied to a model version in your commit log the security side: when something blows up in prod, you want to say "the prompt was version X, model was Sonnet 4.6.1, last eval pass rate was 94%." not "I think we deployed on Tuesday?" the first is an incident report. the second is a resignation letter I've lost more agents to "I changed 3 prompts in one session and broke something" than to any actual bug 4. VISIBILITY: mitmproxy in front of every LLM call it's basically a wiretap for your agent. install it, point your agent through it, and now you see every conversation your agent has with the model in real time what actually shows up: - every silent retry your SDK sneaks in when a call fails - the full prompt being sent (including any creds you accidentally embedded) - what the model returns BEFORE your code reacts to it - exact token cost per call, per tool, per loop iteration - responses that quietly trigger your code into doing something you didn't intend, this is where prompt injection lives the part nobody talks about: if a website your agent scraped slipped instructions into its data, mitmproxy is how you SEE the moment your agent decides to follow them. without this layer, you're trusting your agent did the right thing, not verifying I shipped 3 agents before adding this. I have no honest idea what they were doing in production 5. EVALS: inspect-ai (the framework the labs actually use) an eval framework is what tells you "this agent works" with numbers instead of vibes. inspect-ai is the one Anthropic, DeepMind, and the UK AI Safety Institute use for the eval reports you read in their papers. open source, MIT licensed what your homegrown version won't have: - run the same task across 5 different models and compare scores side by side - pre-built tests for risky agent behavior (lying, manipulating, misusing tools) - proper structure for evaluating tool-using agents, not just chat - repeatable scoring, the same input always gets graded the same way - reproducible eval seeds, so a flaky test is actually flaky and not just unlucky I wrote my own eval harness 4 times across 4 projects. threw it out 4 times if you ever want to say "my agent passes safety checks" out loud, the check has to come from a framework someone else can re-run. this is that framework the move that ties this together: keep a /lessons.md in every repo. every weird agent behavior, every edge case, every config change you find at 2am, write it down you will not remember it. you'll come back in 3 weeks and the lessons file is the only reason you still know what's going on lock these 5, keep the lessons file, your next agentic system takes 2 days instead of 2 months p.s. half of "AI agent" content online is people who've never run mitmproxy on their own loop. they don't actually know what their agent is doing. they're shipping demo videos. don't be that guy

Password manager CLIs might be the most underrated tool after AI coding agents. Recently, I’ve been calling the 1Password CLI directly from Claude Code to back up dev environment secrets. 1Password also has a CLI Activity page that records AI tool usage. Looking back on history, I realized how important visibility is. Thank you @1Password