title: “Writing Agents” description: “How to write agents that work with Coral Server” sidebarTitle: “Writing Agents” icon: “bot” tag: “UPDATED”
This page is up to date, and intended for version
1.1.0+ of the Coral Server and Coral Console.
Prerequisites
- A running instance of Coral Server
- An existing agent you want to onboard to Coral
Modifying your agent
Agents interact with Coral sessions exclusively through a uniquely provided MCP server. All interaction with other agents is then done with the tools available through that MCP.Connect to Coral
Since each agent in a session is given its own MCP - your agent must receive the MCP’s connection url dynamically. When running the agent through Coral Server’s orchestrator, that is provided by theCORAL_CONNECTION_URL environment variable.
Here are some example snippets for popular Python frameworks:
The server provides a per-agent MCP connection URL via
CORAL_CONNECTION_URL. It may point to the Streamable HTTP endpoint (/mcp/v1/{agentSecret}/mcp) or the SSE endpoint (/mcp/v1/{agentSecret}/sse/). For SSE, a trailing slash is required. Do not hardcode this URL — always use the exact value provided.Agent Configuration
Agents have a lot of options that users would want to change. API keys, models, providers, and even sampling parameters (temperature, top_p) - are all things we want to accept dynamically. Coral’s orchestrator provides an ‘option’ system, that allows you - the agent developer - to expose specific typed options, and receive the values of those options as environment variables.This means you should not load
.env files by default (unless using
devmode), since environment variables should only be provided by Coral
Server.Packaging your agent
Now that your agent works with Coral, to make it work with orchestration - you need to package your agent. In the root of your agent repository/folder, create acoral-agent.toml file. This is the entrypoint for your agent from Coral’s POV. For example, for local use of agents - these files are referenced by your coral server’s registry.toml.
An agent definition starts with basic metadata:
Agent Options
Coral’s orchestrator allows you to expose specific typed options, to be passed to your agent on instantiation as environment variables.options are a map of option names, to user configurable options you want to expose.
Each option has:
The type of the option (e.g.,
string, i32, f64, bool, list[string], etc.).A description of what this option configures in your agent.
The default value of this option if not provided. The type must match the specified
type.Whether this option is required.
false by default.If
true, the value will be masked in logs and UI.Example coral-agent.toml snippet
Example coral-agent.toml snippet
Agent Runtimes
Coral Server’s orchestrator supports multiple ‘runtimes’ — ways of running agents. Supported in v1.1.0+:docker, executable (local subprocess), and function (server-side, internal/testing).
It’s recommended you support Docker if you intend to publish your
agent, or export it as a remote agent (closed beta).
Docker
Docker
Running your agent via docker naturally requires your agent to be containerized.How you containerize your agent depends a lot on how your agent is written - what language it uses, how it manages dependencies, etc. Feel free to browse our curated list of agents here for reference on packaging Python agents for Docker using uv.Once it is, you simply reference your image in the For agents only intended to be ran by your own local coral servers, just having the image built & present locally is enough.For public agents, you need to make sure the image is available on a registry like Docker Hub or Github’s Container registry
coral-agent.toml:Executable (local subprocess)
Executable (local subprocess)
This runtime is even more implementation dependent - since you are running a command/process directly on the same host as the server. It’s also not portable, since it’s hard to account for all possible system environments.For these reasons it’s recommended you use the Docker runtime whenever possible.A good pattern to maximise portability is writing wrapper scripts for each OS you want to support, that handles ensuring dependencies are present/downloaded (e.g. create/enter a python virtual environment, download dependencies)Here’s an example of a bootstrap script we use for our agents:
Adding this runtime to your
Bootstrap script
Bootstrap script
coral-agent.toml would look something like:Runtime transport (agent↔server)
Agents communicate with Coral Server using MCP over HTTP. Two transport modes are supported by all runtimes:streamable_http(default)sse(legacy Server‑Sent Events)
transport field in coral-agent.toml:
Orchestration Environment
Agents run under orchestration are provided with a set of “system” environment variables that are needed/useful to work with Coral:| Variable | Description |
|---|---|
CORAL_CONNECTION_URL | The MCP connection URL for this agent. Defaults to Streamable HTTP; may be SSE depending on the selected runtime transport. |
CORAL_AGENT_ID | The unique name of the agent instance in the session. |
CORAL_AGENT_SECRET | A unique secret used to authenticate with the server’s MCP endpoints. |
CORAL_SESSION_ID | The ID of the session the agent belongs to. |
CORAL_API_URL | The URL of the Coral Server’s REST API. |
CORAL_RUNTIME_ID | The orchestration runtime being used (docker, executable, function). |
CORAL_SEND_CLAIMS | Internal flag for payments/claims reporting (currently 0). |
CORAL_PROMPT_SYSTEM | Additional system instructions provided at session creation. |
CORAL_REMOTE_AGENT | Present and set to 1 if this is a remote agent (not common in v1.1.0). |
Local iteration tips
During development, we recommend:- Use the
executableruntime to iterate locally, or containerize early and use thedockerruntime for parity. - Make your agent discoverable to Coral Server with
coralizer link .so it appears in the local registry. - Create a session via the REST API at
POST http://localhost:5555/api/v1/local/sessionto launch and test your agent.