# Invoke Agent

`POST /v1/agent/invoke`

Send a message to an agent from your own app or service.

## Authentication

Send your workspace API key in the `Authorization` header.

```bash
Authorization: Bearer YOUR_API_KEY
```

## Request body

Open an agent in the editor and click **Code Snippet** to see the current public request shape in Fetch Hive.

| Field       | Type    | Required | Description                                                                                                                                                                                                                    |
| ----------- | ------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `agent`     | string  | Yes      | The agent ID                                                                                                                                                                                                                   |
| `message`   | string  | Yes      | The message you want to send                                                                                                                                                                                                   |
| `streaming` | boolean | No       | Stream response events instead of waiting for one final JSON response                                                                                                                                                          |
| `thread_id` | string  | No       | An arbitrary string identifying the conversation thread. Fetch Hive creates a new thread on first use and resumes it on subsequent calls with the same value. Ideal for persistent, multi-turn conversations.                  |
| `messages`  | array   | No       | Previous conversation turns to use as context without persisting history to the database. Each item: `{ "content": string, "role": "user" \| "assistant" \| "system" }`. Use this when you manage conversation state yourself. |

The code snippet dialog uses this body shape:

```json
{
  "agent": "AGENT_UUID",
  "message": "Your message here",
  "streaming": true
}
```

When using `thread_id` for persistent conversations:

```json
{
  "agent": "AGENT_UUID",
  "message": "What did we discuss last time?",
  "streaming": true,
  "thread_id": "user-456-support-session"
}
```

When using `messages` for caller-managed (stateless) history:

```json
{
  "agent": "AGENT_UUID",
  "message": "What else should I know?",
  "streaming": true,
  "messages": [
    { "content": "What are the latest AI trends?", "role": "user" },
    { "content": "Teams are focusing on evals, routing, and observability.", "role": "assistant" }
  ]
}
```

## Response

If `streaming` is `true`, Fetch Hive returns a stream of events.

Example reasoning event:

```json
{
  "request_id": "req_019d52846ea37682b03522fd0695cc43",
  "type": "reasoning",
  "response": "Looking at the latest model releases..."
}
```

Example response event:

```json
{
  "request_id": "req_019d52846ea37682b03522fd0695cc43",
  "type": "response",
  "response": "Teams are standardizing around evals, routing, and observability.",
  "done": false
}
```

Example tool event:

```json
{
  "request_id": "req_019d52846ea37682b03522fd0695cc43",
  "type": "tool",
  "tool_id": "tool_123",
  "tool": "google_search",
  "tool_input": {
    "query": "latest AI infrastructure trends 2026"
  },
  "observation": {
    "results": []
  }
}
```

Example final usage event:

```json
{
  "request_id": "req_019d52846ea37682b03522fd0695cc43",
  "type": "usage",
  "usage": {
    "duration": 4.79230260848999,
    "input_tokens": {
      "total_tokens": 24,
      "cached_tokens": 0
    },
    "output_tokens": {
      "total_tokens": 170,
      "reasoning_tokens": 64
    },
    "total_tokens": 194
  },
  "stop_reason": "completed"
}
```

If `streaming` is `false`, Fetch Hive returns one JSON response.

```json
{
  "request_id": "req_019d528660dd7e22b15e5b13a1931c50",
  "model": "gpt-5-nano-2025-08-07",
  "duration": 4.641960144042969,
  "response": "Teams are moving from simple wrappers to systems with evals, tool routing, and tighter cost controls.",
  "reasoning": "The request asks for a short summary of current infrastructure trends.",
  "usage": {
    "input_tokens": {
      "total_tokens": 24,
      "cached_tokens": 0
    },
    "output_tokens": {
      "total_tokens": 187,
      "reasoning_tokens": 64
    },
    "total_tokens": 211
  },
  "stop_reason": "completed"
}
```

## Example

```bash
curl 'https://api.fetchhive.com/v1/agent/invoke' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json' \
  --data-raw '{
    "agent": "AGENT_UUID",
    "message": "Summarize the latest AI infrastructure trends",
    "streaming": true
  }' \
  --compressed
```

## Related

* See [Authentication](/api-reference/authentication.md) for API key setup
* See [Agents](https://github.com/Jellyfishboy/fetchhive-api/blob/app-v3/LIVE_DOCS/api-reference/agents.md) for agent resource endpoints
* See [Testing with Chat](/agents/testing-with-chat.md) for the in-editor testing flow
* See [Run with API](/agents/run-with-api.md) for an agent-focused guide


---

# 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.fetchhive.com/api-reference/invoke-agent.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.