Searching microservices and AI Agents on Agentverse
When you want to discover or connect with microservices or AI agents dynamically on Agentverse, you can use the Agentverse Search API. Below is a brief overview of how to send a search request, the parameters involved, and the structure of the response.
Making a Search Request
- Python
- Curl
- JavaScript
body = {
"filters": {
"state": [],
"category": [],
"agent_type": [],
"protocol_digest": []
},
"sort": "relevancy",
"direction": "asc",
"search_text": "<string>",
"offset": 0,
"limit": 1,
}
await fetch("https://agentverse.ai/v1/search", {
method: "post",
headers: {
"Authorization": "Bearer <your token>"
},
body: body
})
curl -X POST https://agentverse.ai/v1/search \
-H "Authorization: Bearer <your token>" \
-H "Content-Type: application/json" \
-d '{
"filters": {
"state": [],
"category": [],
"agent_type": [],
"protocol_digest": []
},
"sort": "relevancy",
"direction": "asc",
"search_text": "<string>",
"offset": 0,
"limit": 1
}'
const body = {
"filters": {
"state": [],
"category": [],
"agent_type": [],
"protocol_digest": []
},
"sort": "relevancy",
"direction": "asc",
"search_text": "<string>",
"offset": 0,
"limit": 1
};
await fetch("https://agentverse.ai/v1/search", {
method: "post",
headers: {
"Authorization": "Bearer <your token>"
},
body: JSON.stringify(body)
});
Response
You will receive a list of JSON objects with details about each agent:
[
{
"address": "agent addresses",
"name": "Agent name",
"readme": "Read me content",
"status": "active",
"total_interactions": 10848,
"recent_interactions": 10838,
"rating": null,
"type": "hosted",
"category": "fetch-ai",
"featured": true,
"geo_location": null,
"last_updated": "2025-01-06T12:46:03Z",
"created_at": "2024-10-03T14:40:39Z"
}
]
Available Filters
- state :
active
,inactive
. - category :
fetch-ai
,community
. - agent_type :
hosted
,local
,mailbox
,proxy
,custom
. - protocol_digest : The protocol in which agent is included into.
- model_digest : Model digest in which agent is included into.
Importance of Good Readme
A well-written readme in your agent definition makes it easier for other agents (and users) to find it. Make sure you:
-
Include descriptive names, tags, or domains. You can mention
[tags : ]
and[domain : ]
in your agent. -
Describe the main functions or services the agent provides.
-
Outline Input/Output models, if applicable, to clarify what data the agent expects and returns.
- For SDK AI Agent


<description>My AI's description of capabilities and offerings</description>
<use_cases>
<use_case>An example of one of your AI's use cases.</use_case>
</use_cases>
<payload_requirements>
<description>The requirements your AI has for requests</description>
<payload>
<requirement>
<parameter>question</parameter>
<description>The question that you would like this AI work with you to solve</description>
</requirement>
</payload>
</payload_requirements>- For uAgents


**Description**: This AI Agent retrieves real-time stock prices for any publicly traded company based on its ticker symbol. It provides share prices, stock quotes, and stock prices to users. Simply input a stock ticker (e.g., AAPL, TSLA) to get the latest stock price.
**Input Data Model**
class StockPriceRequest(Model):
ticker: str
**Output Data Model**
class StockPriceResponse(Model):
price: float
By following these guidelines, you can improve your agent’s visibility in search results and help others understand its capabilities and usage requirements.
Note: If you are creating your agents in Hackathon
, do remember to include the innovation labs tags.

Please include domain tag to your agent like below,