ChatGPT Plugin

camelRun

Build and run AI agents

Brand: Unknown

Category: Pending
Primary Subcategory: Pending

Integration details

Description

camelRun is camelAI's hosted runtime for AI agents. Connect your camelRun account to create agents from a plain-language description, give them built-in tools such as web search, run them and read their replies, and deploy agent.yaml manifests that keep an agent's configuration as a reusable, versioned definition. Agents are durable: each keeps its history until you delete it, can wake itself on a schedule, and can stop to ask you a question or for an approval, which you answer from the conversation. It is for developers and teams who build agents for their products or their own work and want to try, adjust and manage them without leaving the conversation. The plugin acts only on the camelRun account you sign in with, and only on its agents, definitions and schedules. Runs use your account's credit. It does not manage billing, API tokens or provider keys; do those in the camelRun console. Tool servers that need secrets are best deployed with the camelrun CLI, which reads them from its environment, so credentials never pass through the conversation. Deleting an agent or definition cannot be undone, so you are asked to confirm first.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: Pending
Primary Subcategory: Pending
Secondary Subcategories: None listed
Brand: Unknown
Access: Account required
First tracked: 2026-10-17
Tool count: 23
Geography: US

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Primary Subcategory

Competitive lineup

No Primary Subcategory assigned yetOnce camelRun has a Primary Subcategory, the Plugins and Connectors it competes with will appear here with their scores.

Tools

23 tools agents can invoke

Wake an agent later with a message: once (inSeconds or at), or repeatedly (everySeconds, at least 60). Each wake-up is a run that uses the account's model credit.
add_schedule
Answer an input and wait for the run it resumes. An approval takes true or false; a question the chosen label or your own words (several questions: {"<question>": "<answer>"}); a form its fields; "decline" declines. Only answer with what the person decided: an answer cannot be taken back, and an approval lets the agent go ahead with what it asked to do.
answer_input
Change one agent's model, system prompt, prompt addition or thinking level between its runs, replacing the current values; its history is kept.
configure_agent
Make the agent for a key: from a definition, or with its own model and system prompt. The same key is the same agent, so calling it again for a key that exists updates that agent to the configuration given, keeping its history. It lives until deleted.
create_agent
Delete an agent: it stops at once, and its history and files are purged; this cannot be undone, so confirm with the person first. Its key makes a fresh agent next time.
delete_agent
Delete a definition and its revisions; this cannot be undone, so confirm with the person first. Agents made from it keep running as they are.
delete_definition
Cancel a scheduled wake-up; this cannot be undone.
delete_schedule
Deploy agent manifests: upsert each definition by its key (a new revision only when it changed, replacing the current one) and make or update the keyed agents it lists. Use dryRun first to show what would change. Give `manifest`, the YAML itself (as an agent.yaml holds it). This server reads no files and no environment variables: put the system prompt in systemPrompt and any OpenAPI spec in spec. Never ask a person to paste credentials into the conversation: a manifest whose tool servers need secrets is deployed with the camelrun CLI, which reads them from its environment.
deploy
Make a new agent from an existing one: the same configuration, a copy of its conversation and a copy of its files, each its own from then on, so the copy can try another direction while the original stays as it was. By default the copy ends with the last turn that finished; atMessage ends it earlier. With a key it lives until deleted, and calling again with the same key returns the same fork.
fork_agent
An agent's configuration, the definition revision it has, and every source of its tools with what each offers. Changes nothing.
get_agent
A definition in full: model, system prompt, built-ins and tool sources (never their credentials). Changes nothing.
get_definition
A run's status and result, waiting up to `wait` seconds for it to end. Changes nothing.
get_run
The agents made from a definition, and the revision each has. Changes nothing.
definition_agents
The account's agents: key, id, name and model. `loaded` is whether the agent is in a runtime's memory now, idle or not; it says nothing about whether a run is going (run_agent and get_run do). `toolsConnected` is whether an application serving its attached tools is connected. Changes nothing.
list_agents
The account's definitions (reusable agent configurations): id, key, revision, model and built-in tools. Changes nothing.
list_definitions
The models agents can use, with context window, reasoning support, price and toolCallStreaming (true: tool-call arguments stream as written, so a page can render a section while it is written; false: they arrive in one piece; "unknown": not measured): pass a model's id as `model` to create_agent, configure_agent or a manifest. Changes nothing.
list_models
Questions, approvals and forms waiting on a person: one agent's, or every agent's. Changes nothing.
list_inputs
An agent's scheduled wake-ups. Changes nothing.
list_schedules
An agent's latest messages, in whole turns: text, tool calls and tool results. Changes nothing.
agent_history
camelRun's own documentation as Markdown: with no path, the index (llms.txt); else a page such as guides/definitions.md, guides/tools.md or reference/cli.md. Changes nothing.
read_docs
Send an agent a message and wait for its run: the reply, the input it waits on, or why it failed. A run still going after `wait` seconds comes back as running; call get_run. The agent acts with the tools it was given (such as web search and its MCP servers), and the run uses the account's model credit.
run_agent
The camelRun account (tenant) these credentials act for, the runtime's URL and the default model. Changes nothing.
whoami
Stop an agent's running turn; the turn's unfinished work is cancelled. The agent and its history stay.
abort_agent

FAQs

camelRun ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve camelRun's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.