Agent editor

The agent and its tools, as nodes.
Select the root node to open Agent Settings, or any tool node to configure it. Add a tool from the header and it appears on the canvas with its own settings sheet.
AI agent builder
Fetch Hive is a no-code AI agent builder. Give an agent a model, instructions, tools, and knowledge. It picks the right tool for each request, calls your workflows and connected apps, remembers the thread, and pauses for your approval before anything with side effects. Test it in chat, then run it from your code or the AI assistant you already work in.
Free Developer plan ยท No card required ยท Agent templates you can clone in one click

01
ANATOMY
An AI agent is not a fixed path. It reads the request, decides which tool to use next, reads the result, and keeps going until it has an answer. You set the boundaries: the model, the instruction prompt, the tools it may call, and what needs your approval.
01
Pick an OpenAI, Anthropic, Gemini, xAI, Perplexity, or Kimi model. Set temperature or reasoning effort, max tokens, and an instruction prompt that says what the agent is for and how it should behave.
02
Add web search, code execution, image generation, or any app connected under Integrations. The agent reads each toolโs description and decides when to call it.
03
Hand a deployed workflow to the agent as a tool, or let one agent call another. Each call runs with its own logs and trace, nested under the parent run.
04
Attach a knowledge base so answers draw on your own documents. Pass a thread_id and Fetch Hive keeps the conversation history for you between calls.
02
BUILD
The agent editor shows the root agent and every tool as nodes on one canvas. Change a setting, add a tool, and send a test message from the same screen. Test chats are not saved, so you can iterate freely.

The agent and its tools, as nodes.
Select the root node to open Agent Settings, or any tool node to configure it. Add a tool from the header and it appears on the canvas with its own settings sheet.

Talk to it before you ship it.
Open Chat in the editor header and send a message. You see the reply, the tools it called, and the tokens it used. Nothing is saved, so you can push on it until it behaves.
03
DEPLOY
Every saved agent has one invoke endpoint. Your code, a webhook from another service, or your assistant over MCP all talk to the same agent, and a thread_id turns a single message into a conversation.
Pass any string as thread_id, such as a user id or a ticket number. Fetch Hive creates the thread on the first call and resumes it on every call after, with the history included.
Let an external service start an agent run with the agentโs own webhook secret instead of your API key. The reply is delivered to your callback URL and signed.
Invoke an agent with your API key from cURL or the Python, Node.js, Ruby, and PHP SDKs. Stream the response as it is generated, or wait for the final JSON.
When a tool needs approval, the response comes back as awaiting approval with a review link. Allow once or deny from the dashboard or the API, and the run continues.
agent invoke ยท support-triage
# send a message to the agent from any system that can POST
$ curl https://api.fetchhive.com/v1/agent/invoke \
-H โAuthorization: Bearer <api key>โ \
-d โ{ โagentโ: โ<agent id>โ, โthread_idโ: โticket-42โ,
โmessageโ: โSummarize this ticket and draft a replyโ }โ
โ req_01HZโฆ streaming ยท thread ticket-42 resumed with 3 earlier turns
Status
awaiting approval
Thread
ticket-42 ยท history loaded by Fetch Hive
Tools called
search_tickets ยท knowledge_search ยท draft_reply (needs approval)
Next
allow once or deny, then the run continues
THREADS AND APPROVALS
A thread is the memory of a conversation, under any id you choose. An approval is a pause the agent cannot skip. Together they let an agent work on your behalf for days without ever acting without you.
Reuse a thread_id and the agent picks up where it left off
Or send the earlier turns yourself and nothing is stored
Approvals expire, carry a review link, and are logged with who decided
Always allow stays in the dashboard, never in an API call
04
INTEGRATE
Connect your apps once under Integrations and add them to any agent. 73 live providers, more than 6,400 agent tools, and every call the agent decides to make is recorded in its run trace.
6,400+
AGENT TOOLS
Actions an agent can call today
73
LIVE PROVIDERS
Apps connected once, reused by every agent
6
MODEL PROVIDERS
OpenAI, Anthropic, Gemini, xAI, Perplexity, and Kimi
Customer email
Message in
Support agent
Decides and acts
Ticket in Zendesk
Tool call
Reply drafted
Awaiting approval
05
CONNECT
Fetch Hive ships an MCP server. Connect Claude, ChatGPT, Cursor, or Codex once, and your assistant can find, build, configure, and run agents in plain language. Every run is logged like any other.
What your assistant can do once it is connected
Find and read any agent in your workspace, tools and knowledge included
Send a message with the cost quoted first, then approve it in the chat
Build a new agent from a sentence, or clone and tweak a template
Change the model, instructions, tools, or knowledge, with undo
Approve or deny a paused tool call from the chat
Open the run trace and the reply without leaving the conversation
WORKS WITH

Sign in once with OAuth. Nothing runs without your yes.
06
OBSERVE
Agent Logs keep each run with its model, tokens, tasks, tool calls, and the full trace, with sub-agent and workflow calls nested under the parent. Filter by provider, model, API key, or your own metadata.
01
The task
Produce a company research brief with sources. The input is a company URL; the expected output is a one-page document your team can read.
02
The execution
Every model call, tool call, duration, and recorded cost. Open a meaningful step to see its input and output.
03
The output
A readable excerpt from the resulting brief, with sources where supported, next to the run summary.


Every run records:
Every message in and out, with the thread it belongs to
Each tool call, its arguments, result, and duration
Tokens and cost, broken down by parent agent, sub-agents, and tools
Approval decisions, who made them, and when
Value is a human judgement. The run gives you every decision the agent made and the recorded cost of making it, and the same trace is what your assistant reads over MCP.
07
START FASTER
Most agents start as a copy of one that already works. Or describe what you need and Fetch Hive drafts the agent, its instructions, and its tools for you to review.
Templates ยท Free to clone
I WANT TO
Browse agents built by Fetch Hive and the community. Clone one into your workspace, swap the model or the tools, and it is yours.
Filter the marketplace to agents only
Keeps the instructions and built-in tools; reconnect apps in your workspace
Every template shows how many people use it
No account needed to browse
Describe it
I WANT TO
Tell Fetch Hive what the agent should do, in the dashboard or from your AI assistant. It asks what it needs to know, drafts the instructions, picks the tools, and saves a draft you can test right away.
Answer a few questions and review the draft before anything runs
Test it in chat, then invoke it from your code
Change anything later in the editor
Free Developer plan
MOST USED AGENT TEMPLATES
PART OF THE FETCH HIVE PLATFORM
Connect Slack, Zendesk, Google, HubSpot, and the rest once under Integrations, and every agent can use them. The same workspace runs your workflows, so an agent can hand a task to one as a tool.
FAQ
Everything else is in the agent docs.
An AI agent builder is a tool for creating AI agents without writing the orchestration code yourself. In Fetch Hive you pick a model, write the instructions, and add tools, knowledge, and approvals in a visual editor. No code is needed to build or test an agent, and the same agent can be called from the API when you are ready.






