The Setup
Imagine your AI agent gets a task: "Research our product's competitors on X, pull reviews from Amazon, check prices across marketplaces." Until recently, doing this required: finding the right APIs, registering, getting keys, writing integrations, normalizing different response formats — separately for every data source.
Monid offers a different path. The agent describes what it needs. Monid finds the right endpoint, checks the price, executes the request, and returns a structured result. One balance, one auth, the full tool catalog.
This sounds like a convenient DevTool. But the idea behind it is much bigger: the first marketplace where the default buyer is a program, not a person.
How It Works
Three steps for the agent
Monid's architecture maps to three verbs:
Discover — the agent asks: "What do you have for scraping X?" Monid returns a list of available tools with descriptions.
Inspect — the agent reviews the schema for a specific tool: what parameters it accepts, what it returns, how much one call costs.
Run — the agent executes the request. Monid handles auth with the provider, error handling, billing, and delivers the result in a structured format.
The user (or agent) pays only for actual calls — classic pay-per-use.
Four connection methods
Monid is available via:
- MCP (Model Context Protocol) at
mcp.monid.ai/v1— works directly from Claude.ai and ChatGPT with no extra code - Skill — setup instructions for Claude Code or Cursor
- CLI — npm package for developers and terminal-based agents
- REST API — direct HTTP calls with a bearer token
The multi-channel approach isn't accidental. Monid covers the full spectrum from "human wanting to try something quickly" to "agent making 10,000 calls per hour in autonomous mode."
The OpenRouter analogy
OpenRouter is a router for AI models. Instead of writing separate integrations for OpenAI, Anthropic, Google — you write one call to OpenRouter, and it picks the provider, manages quotas, and issues a unified bill.
Monid does the same thing, but for tools and data sources. Not AI models — APIs, databases, web sources, services. The agent doesn't need to know how each provider works. It describes the need; Monid handles the details.
The distinction matters: OpenRouter solves "which brain to use." Monid solves "which hands to use."
The Numbers
Monid is an early-stage startup; no revenue figures are public. But the numbers around it speak for themselves:
| Metric | Value |
|---|---|
| AI agent market (2025) | $7.8B |
| Projected by 2030 | $52.6B (46% CAGR) |
| B2B purchases via agents by 2028 | $15T (Gartner) |
| Orgs scaling agents in 2025 | 23% |
| VC into agent startups in 2024 | $3.8B |
| Enterprise apps with embedded agents by 2026 | 40% (Gartner forecast) |
Context: Gartner projects that by 2028, AI agents will participate in $15 trillion of B2B purchasing. This doesn't mean agents "replace" humans — but they become intermediaries in an enormous volume of transactions. Someone has to be the infrastructure for those intermediaries.
Why It Works
1. B2A is a new category, not an evolution of B2B
B2B marketing is engineered for humans who make decisions. Landing pages, case studies, demo calls, sales reps, nurture sequences — all of it is built to persuade a person.
When the buyer is an AI agent, the rules change:
- The agent doesn't need a nice landing page. It needs documentation with a clear API schema.
- The agent doesn't read G2 reviews. It checks latency, uptime, and error format.
- The agent doesn't negotiate a contract. It reads the pricing endpoint and decides in milliseconds.
- The agent isn't brand loyal. It's loyal to results within a given budget.
Monid builds infrastructure for exactly this logic: a data provider publishes their tool in the catalog with a machine-readable description, per-call price, and schema — and agents start using it with zero human involvement on either side.
2. Two-sided marketplace network effects
Monid is a marketplace with two sides:
- Supply: tool providers (API companies, data services, indie developers)
- Demand: AI agents (and the developers who build them)
The mechanics are the same as Stripe Marketplace or AWS Marketplace: more tools in the catalog means Monid is more useful to agents. More agents means it's more interesting for providers to list their tools. As long as the catalog grows daily, the flywheel spins.
3. Trust and payment as infrastructure
Monid explicitly positions itself as the solution to the trust, payment, and fulfillment problem between an agent and a provider. This isn't trivial.
When an agent wants to call a third-party API, it needs to:
- Verify the provider is reliable
- Have credits or an API key with that provider
- Trust the response formats
- Handle errors and retries
Monid absorbs all of that complexity. The agent works with one trusted layer — the way a person works with one credit card instead of carrying cash to every vendor.
4. MCP as a strategic bet
MCP (Model Context Protocol) — Anthropic's standard for connecting tools to AI agents — is fast becoming the de facto protocol for agent-tool interaction. Claude, ChatGPT, Cursor, Claude Code — every major agentic environment supports MCP.
Monid builds around MCP as its primary protocol. Smart move: don't invent a new standard, ride the industry standard and become an "aggregator on top of the aggregator."
5. Pay-per-use removes friction for agents
Subscription models work poorly for autonomous agents: the agent doesn't know in advance how many tools it'll need or when. Pay-per-use perfectly matches the nature of agentic work: run a task, pay for the resources actually used.
For the developer: you can launch an agent experiment with $5 in balance and not think about subscriptions, limits, or pricing tiers.
Why This Is More Interesting Than It Looks
The early-internet analogy
In the 1990s, websites appeared as content for humans. Then search engines emerged — and a new layer appeared: infrastructure that websites had to account for to be found. SEO became mandatory for any business online.
A similar shift is happening now. Agents are becoming intermediaries between need and execution. An API provider that doesn't appear in an "agent catalog" becomes invisible — like a website without SEO in 2005.
Monid is claiming the role of that "search engine" — but for machine-to-machine interaction.
Who wins is an open question
Being honest here: Monid isn't the only player. Composio, Toolhouse, AgentOps, Zapier's MCP layer — everyone is building similar infrastructure. The question is who:
- Reaches critical tool mass first
- Becomes the default choice for popular agent frameworks
- Builds the best DX for agents
In a forming market, the winner is the one who moves fastest.
How to Apply This as a Solo Founder
The Monid model opens several concrete opportunities right now.
Opportunity 1: Become a tool provider
If you have access to unique data or automation — publish it as a tool in an agent marketplace. Scraping specific sites, access to niche databases, industry-specific APIs — all of this can be a pay-per-use service.
The customer isn't a human with a credit card; it's an agent with a balance. Marketing isn't needed: what you need is good documentation and a sensible per-call price.
Opportunity 2: Agent-native SaaS
Instead of selling "software" to people, sell an "agent" with an outcome. "$99/month for a tool" becomes "$0.05 per successful call" — and your customer's agent decides how often to use your service.
This shifts the product mindset: not "how many features are in each tier," but "how reliable is my API and how structured is my output."
Opportunity 3: Vertical aggregator
Monid is a horizontal platform. But you can build a vertical analog: "tool marketplace for real estate AI agents," "tool marketplace for fintech agents." Narrow niche, deep expertise, custom integrations.
B2A product principles
If you're building a product where the buyer is an agent:
Documentation beats landing pages. Your OpenAPI schema, request/response examples, and edge case descriptions are your "marketing."
Structured output is non-negotiable. Agents can't parse "text with data" — they need JSON with a predictable schema.
Reliability over features. 99.9% uptime and predictable error handling matter more than a rich feature set.
Per-call pricing. Not subscriptions, not bundles — pay for use. The agent optimizes costs itself.
Zero-trust by default. The agent doesn't "know" you. Every call should be verified, every response validated.
Where to start right now
- Install the Monid CLI:
npm install -g monid - Browse the tool catalog — it's a map of current demand
- If you have niche data or automation, try publishing your first tool
- In parallel: start building agents that use others' tools — it teaches you what DX actually works
B2A isn't a distant future. Gartner projects 40% of enterprise applications will have embedded agents by 2026. That means within 12–18 months, a significant share of API calls on the internet will be generated by programs, not people.
The infrastructure for this is being built right now. Those who see it first will claim their positions earliest.
