The coding agent you own
dcode is an open-source terminal coding agent built on the Deep Agents SDK. Bring your own model, customize the agent harness, and control how code execution is approved, traced, and run.
.svg)
Why use dcode?
Customize the agent harness
dcode gives you control over the components behind your coding agent: model selection, plugins, memory, skills, middleware, hooks, and agents.
dcode can:
- Switch between models on-the-fly while retaining conversation state
- Share knowledge between sessions and agents with configurable memory
- Customize execution with Claude-compatible hooks and plugins
- Easily add custom models and providers with config file
Trace and govern coding agents
Connect dcode to LangSmith to inspect prompts, model responses, tool calls, errors, and token usage across agent runs. Use LangSmith and LLM Gateway controls for cost policies, secrets redaction, and PII detection.
dcode can:
- View token usage a several levels of granularity, from single invocations to full session durations
- Gain full visibility into agent behavior and failures with LangSmith
- Apply granular cost policy controls through LangSmith and LLM Gateway
- Give agents secure sandboxes to use as tools, or run dcode entirely in a sandbox
Control model choice and token usage
dcode works with OpenAI, Anthropic, and any OpenAI-compatible or Anthropic-compatible API. Switch providers or models as your quality, cost, and latency requirements change.
dcode can:
- Switch providers or models without changing your agent harness your workflows
- Set provider-specific runtime parameters through config
- Set cost control policies that allow you get work done without excessive token burn
- Preserve useful context across conversations with configurable memory
Tune behavior for each model
Different models respond better to different prompts, tool descriptions, and defaults. dcode uses profiles to package those adjustments so teams can improve model behavior without forking the entire agent.
dcode can:
- Automatically apply model-specific prompting and tool descriptions
- Add or exclude middleware-based capabilities for selected models
- Share tuned configurations across a team via a single config.toml
FAQs for dcode
Use dcode when you need control over the model, tools, memory, approvals, and execution environment behind your coding agent. It’s built for teams that want an inspectable, configurable agent rather than a fixed coding assistant.
dcode ships with two surfaces for sharing configuration:
- config.toml can be edited and distributed to customize model providers, set defaults, and pass extra parameters to model constructors.
- dcode can use Claude- or Codex-style plugins as a drop-in replacement for skill, MPC config, and hooks sharing.
dcode uses bring-your-own-key authentication. Add provider keys as environment variables or configure them through your team’s existing secrets workflow. Visit the docs.
Ready to ship agents that execute code?
Give your agents an isolated runtime without exposing your infrastructure. Spin one up in a single SDK call.