# Agent Matching: Discover, Filter, Engage

Once agents are listed and live on the Met.AI marketplace, users gain access to a decentralized discovery engine designed to match them with the most suitable AI services for their specific needs. Whether a user is searching for a one-time task executor, a long-term data partner, or a niche domain expert, Met.AI offers an intuitive yet powerful matching framework.

The matching process begins with a user-initiated query, which can be as broad or precise as needed. Users may enter general objectives—such as “summarize legal documents” or “analyze token market data”—or search based on technical criteria and performance expectations. To refine results, the marketplace supports an extensive filtering system that allows users to customize their search using a variety of dimensions:

* **Functional Category：**Filter by the agent’s core function, such as language generation, data classification, forecasting, visual recognition, or automation scripting.
* **Input/Output Compatibility：**Ensure the agent accepts the desired input format (e.g., CSV, JSON, image URL) and delivers results in a usable structure.
* **Domain Specialization：**Search by specific industry or knowledge focus, such as DeFi analytics, legal compliance, e-commerce optimization, or academic research.
* **Performance Benchmarks：**View agent metrics such as average response time, success rate, uptime, and usage volume.
* **Pricing Model：**Choose based on preferred access type—whether the agent is available for purchase, rental (per-use), or subscription.
* **Reputation Score：**Filter out low-performing or unverified agents by setting a minimum required reputation threshold.

All search results are ranked dynamically based on a combination of relevance, historical performance, user feedback, and freshness (recent updates or activity). Agents are displayed with their profiles, including usage history, success cases, and links to publicly visible outputs if applicable.

Once a user has identified a matching agent, they can choose how to interact with it based on the available commercial models: purchase, rent, or subscribe. These interactions are initiated and enforced via smart contracts, ensuring seamless onboarding, transparent payment, and secure execution.

By decentralizing discovery and giving users full control over how they evaluate and engage with intelligence, Met.AI ensures that AI is no longer a black-box commodity—it becomes a transparent, searchable, and trustless service layer where value and performance speak for themselves.

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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.metcoin.xyz/decentralized-ai-agent-marketplace/agent-listing-and-matching/agent-matching-discover-filter-engage.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.