agent tools need an OpenRouter layer this could be a HUGE infrastructure opportunity in AI OpenRouter gave developers one place to discover models, call them through the same interface, compare prices and route requests by price, speed and availability one campaign agent might use Firecrawl for research, Stripe for payments, HubSpot for CRM and Slack for communication connecting those providers directly means managing separate accounts, credentials, billing, permissions and tool formats (mega headache) the opportunity is one agent-tool router that manages how agents discover and run actions across those providers: > describe the outcome > discover the right provider > connect the correct company account > see the price and permissions > run the work and verify the result > retry, send it for human review or fall back to another provider this goes beyond an MCP directory. MCPs gives agents a common way to discover and call tools, while the agent-tool router still needs provider success rates, prices, permissions and verified outcomes we are moving from APIs that expose individual product actions toward outcome endpoints an outcome endpoint lets an agent request a finished job while the provider handles the planning, execution, validation and delivery (basically: give the agent the job, get back the finished result + receipt) an agent needs a small set of jobs it can request: > research this market > reconcile this account > launch this campaign > resolve this support ticket > produce this report > update this forecast Firecrawl lets an agent request a research job, while Parallel takes a research task and returns a synthesis with sources Composio and Pipedream aggregate large tool catalogs and handle parts of discovery, account authentication and execution. the official MCP Registry provides shared metadata for public tool servers. x402 is a pay-per-call protocol that lets agents purchase access to compatible endpoints the complete agent-tool router is still missing (we have most of the pieces, nobody seems to own the full route yet) this is where it gets messy: tools are harder to route than models. a model request usually returns text, media or embeddings, while an agent tool can publish a post, refund a payment, contact a customer, delete data or change the state of a company account so the router has to know a lot more than "which endpoint is cheapest": > per-user identity and permissions > human sign-offs for spend and external actions > protection against duplicate writes, plus a way to undo partial changes > logs, receipts and checks that confirm the outcome > routing based on price, speed, reliability and quality > fallback only when providers can safely produce the same result one connection should handle discovery, credentials, approval and access rules, billing and execution, while every agent receives only the account access and actions required for its job for a marketing agent, that could mean selecting a research provider, connecting the client workspace, showing the expected spend, waiting for sign-off before publishing, then returning the live links and receipts to the campaign brain, the files holding the campaign plan and results people use human interfaces to configure the system, approve sensitive actions, monitor work and handle exceptions. agents call outcome endpoints to run approved jobs the open problem is proving the selected provider finished the job before the router accepts the result, retries or safely falls back