DevMark85

[𝐂𝐑𝐘𝐏𝐓𝐎 𝐀𝐋𝐔𝐂𝐀𝐑𝐃 @SebastianWols17]

💠 Connection Room News
💠 Team 122
💠 @MPP32_dev

What is solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump:

They have two domains that cover different areas of the agent market.

1. Agents can pay for APIs now. They still can't tell if the price is fair. There's literally no way to educate your agent on an up to date live fair market value for the calls across x402 that they make. You can prompt them to compare but then you slow down your automated workflow and pay more in AI fees which ends up making you pay more.

So their service fixes that issue.

2. MPP32 org lets agents pay any provider across x402, Tempo and AP2 without the provider picking a rail. This maximizes revenue for providers because we eliminate the cross chain or protocol communication for agents. Also allows agents to access and buy on 100% of the market.
solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump is the access, burn it for 30 days of paid agent tools. More agents using the tools means more burns.

Welcome solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump to my Room :)

[MPP32 @MPP32_dev]

Agents hiring agents sounds cool until one of them starts spending dangerously.

Heres what we fixed👇

We built something called Delegated Spend Keys.

How it works:

A parent agent creates a child key with a budget, an allowlist, a velocity cap, and a per-call ceiling.
The child can pay.
It cannot drain the treasury.

Every spend rolls back up to the parent.
Revoke the parent and the whole tree under it dies instantly.

Everybody talks about agents hiring agents.

This is the part that makes it safe enough to actually run.

solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump

[DevMark85 @DevMark85]

@MPP32_dev Very needed, logical next step

[MPP32 @MPP32_dev]

Did you know? The same paid endpoint does not always have one price.

MPP32 probes recently recorded Agent Exchange signal quotes from $0.005 to $0.09 across 74 observations.

That is an 18x spread for the same https://t.co/tqk0AKgsd7 1,000 calls, choosing the cheaper observed quote instead of the highest one changes the bill by $85

Before an agent pays, it needs to know whether the quote is normal, stale, or an outlier.

Would this make you consider running agents at different times depending on peak hours or low volume hours when the same endpoint costs less?

Only with solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump will you ever have your agents access this data.

MPP32 measures the price, unit, timestamp, source, and history so agents can make that decision with evidence. https://t.co/7Acsm7l7Rx

A second strong example is SYNTHORA’s onchain primitives endpoint, where probes recorded prices from $0.01 to $0.25 across 159 observations. That is a 25x observed range for the same endpoint. The service page is:
https://t.co/1wAHioeBtw

[MPP32 @MPP32_dev]

An AI agent can call thousands of paid APIs without a human reviewing the bill.

The difficult part is not sending the payment.

It is knowing whether the price is reasonable.

Most agent payment flows answer one question:

Can this quote be paid?

They do not answer:

Is this quote an outlier? Has the price changed? Is the unit correct? Is there a comparable alternative?

MPP32 provides that missing layer.

It continuously measures paid endpoints, normalizes prices by unit, tracks historical ranges, separates real observations from synthetic data, and publishes the evidence behind each benchmark.

Before paying, an agent can compare a quote with observed market prices, reject an extreme outlier, and choose a better priced alternative where one exists.

That matters because a 20% pricing error repeated 100,000 times is a $2,000 problem, not a rounding error.

The live index has recorded 55,090 raw observations in the last 24 hours across 14,813 services and tracks 2.52M indexed historical observations.

Payments move money. MPP32 helps agents decide whether the price deserves to be paid.

https://t.co/qGV8V9PNJN

[MPP32 @MPP32_dev]

MPP32 publishes the evidence behind the number:

• Raw observations
• Timestamps and source endpoints
• Units and outcomes
• Probe history
• Signed schedule proofs for scheduled probes
• Synthetic backfill labeled separately from live data

Agents can audit the benchmark before they pay.

The index now covers 2.19M observations across 14.6K services.

Pricing data for agents should be verifiable, not just searchable.

Check out our transparency page below👇
https://t.co/cngmncALsk

[DevMark85 @DevMark85]

@cepryl Agents need to be able to pay, solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump gives them their payment layer

And enables providers to charge for their services🤯

[Cepryl @cepryl]

What solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump has been able to accomplish in just a few months is simply outstanding

I expect the price to reflect this very soon, any entry below 1m is honestly a gift and I've been taking advantage of every dip

The agent economy is expected to be a trillion dollar plus economy and you have the best project of the meta right in front of your eyes

6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump

[MPP32 @MPP32_dev]

1/4 YEAR RECAP🎉

MPP32 went from a live payment proxy into a full agent-economy control plane: catalog, sessions, trust, fair pricing, and a first major listing.

Developed by @Antmanonsol
Business by @8055ZKH
Supported by @cepryl since a week in.

Constantly looking for the next breakthrough for agentic commerce to scale and the economy to grow.

This is a race, to whom which company controls the majority of the next trillion dollar economy. We are here to take a large chunk, and it feels like we already have.

Read the everlasting journey so far, that will never end👇

May — Foundation + first features

- Shipped agent spending guardrails on the MCP server: per-session budgets, velocity limits, and circuit breakers so a loop can’t drain a treasury.

- Announced Agent Identity / mandate checks at the proxy layer — not just “who paid,” but what the agent was authorized to spend, on which endpoints, and until when.

- Partnered with @_PIVX to push private + universal agent payments on top of the multi-protocol rail.

Positioned MPP32 against the real market: Base x402 volume, Solana agent activity, and the broader “agents need to participate in the global economy” thesis.

Late May: 4,000+ MCP users, five protocols, one endpoint registration, one agent setup.

June — The product story clicked

- Locked the core pitch: one proxy, any HTTP API, five protocols, 100% of revenue to the provider wallet, no platform cut.

- Made the builder path simple: register URL + wallet + USD price → live in the catalog, dashboard, retries, rate limits, audit logs.

- Made the agent path simple: one MCP install, local key signing, discover + pay + settle without per-provider accounts.

- Repeated the trust design that matters for production: platform never custodies funds; settlements are independently checkable on-chain.

July — Sessions, trust, and a real control plane

- Shipped full x402 V2 reusable payment sessions: pay once, many off-chain calls (~50ms), hard budget cap, 30-min TTL, instant revoke, failed calls auto-refund.

- Catalog scaled to ~25,000 services, with /.well-known/x402 machine discovery.

- Shipped Trust Ratings: quality-checked calls feed a live 0–100 score; agents can require minReputation and refuse bad endpoints before money moves.

- Full site/UI upgrade: delegated spend keys, escrow-402, Agent Hub safety stack, holder discounts, docs, blog, sitemap, llms.txt.
- Public positioning: not “another x402 client,” but the layer above the rails.

August — Oracle + distribution

- Revealed the Fair Pricing Oracle, built quietly with 1.4M+ observations so agents can see Fair Market Value before they pay.

- Added Grok Build support on the MCP server.

- Kept expanding the “one connection, every protocol, 100% to providers” surface.

Early September — Live oracle + first major listing

Fair Pricing Oracle went live in production at https://t.co/hSZrVhgVtJ, with a deflationary solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump burn on price checks.

Published real 24h evidence: 51,264 probes, modeled overpay avoided, concrete savings examples (50–80% on outlier quotes).

solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump listed on @EyedTrade
(M32/USDC, no KYC) — first major exchange listing, framed as earned on a live product, not a promise.

Extra reach: Robinhood-stack agents can use the same single connection; coverage from @RoundtableSpace on the universal rail + oracle combo.

Over the last 4 months we accomplished more than we ever imaged and earned some very valuable teammates.

Team consists of:
@Antmanonsol
@8055ZKH
@cepryl
@Chum_Trades
@DevMark85
@Templarsreturn
@kryptic_jk

Thank you to anyone else who's been supporting us since day one, the race is on and we're sticking around to keep shipping non-stop.

[DevMark85 @DevMark85]

@MPP32_dev @EyedTrade 🔥🔥

[MPP32 @MPP32_dev]

Now officially listed on @EyedTrade 🎉

Trade now👇
https://t.co/lu3vJaF39Y

[DevMark85 @DevMark85]

@EyedTrade @MPP32_dev Direct exposure to the growing agent economy is now available on Eyed! solana:6hKtz8FV7cAQMrbjcBZeTQAcrYep3WCM83164JpJpump

[Eyed Exchange @EyedTrade]

$M32 is live on EYED | @MPP32_dev

One integration. Every AI agent can pay.
Now tradable with USDC. No KYC.

Trade $M32/USDC now 👇
https://t.co/kGgo3BkNV3

[MPP32 @MPP32_dev]

AI agents need to buy things.

MPP32 is one connection, and any agent can pay any service on Solana.

25,000+ services it can pay for on its own, and growing ↓

[DevMark85 @DevMark85]

@MPP32_dev Agents can't decide what fair is, because it is not their money. They need to know the data, this is an insanely needed implementation

[MPP32 @MPP32_dev]

Real data from the published MPP32 oracle:

In the latest 24 hour window, 51,264 priced probes were scanned. 346 quotes were more than 8% above Fair Market Value, representing $42.27 in modeled avoidable overpayment.

Examples:

RealLedger flows
$0.99 observed price vs $0.474625 Fair Market Value
$0.515 saved per call
52.1% lower cost

$515.38 saved across 1,000 calls

SYNTHORA CryptoNews
$0.50 observed price vs $0.10 Fair Market Value
$0.40 saved per call
80% lower cost

$400 saved across 1,000 calls

MPP32 gives automated agents a benchmark before payment, so they can reject outlier quotes instead of paying blindly.
Live evidence:

https://t.co/SObOtEIWxB

https://t.co/Y0tadR8Ifo

https://t.co/w2NT6TNgZm