In the rapidly evolving landscape of AI coding assistants, developers are constantly seeking more efficient ways to integrate these tools into their workflows. A new open-source project called AgentAPI has caught the attention of the developer community by offering a unified HTTP interface for controlling various AI coding agents including Claude Code, Goose, Aider, and Codex.
Bridging the Gap Between Coding Agents
AgentAPI solves a significant pain point for developers who work with multiple AI coding assistants. Rather than learning different interfaces for each tool, AgentAPI provides a standardized HTTP API that allows programmatic control of these agents. The tool works by running an in-memory terminal emulator that translates API calls into terminal keystrokes and parses the agent's outputs into individual messages.
One community member highlighted the flexibility this approach offers:
I've been using claude code over SSH which also works very well. Even was using it via my home vpn on my phone while on a walk. Seems like you could achieve the same type of experience with this.
This comment underscores the value proposition of AgentAPI: enabling developers to interact with coding agents in ways that fit their specific workflows and environments.
Enabling Novel Integration Patterns
Beyond simple remote access, AgentAPI opens up interesting possibilities for agent collaboration. The tool's ability to control one agent from another has sparked excitement about potential peer programming scenarios. As one user commented, with an MPC (Multi-Party Computation) server, tools like Cursor and Claude Code could potentially collaborate on programming projects.
This capability aligns with AgentAPI's roadmap, which includes potential support for the MCP protocol and the Agent2Agent Protocol. These additions would further enhance the tool's ability to facilitate communication between different AI systems.
AgentAPI Key Features
- Unified HTTP API for controlling multiple coding agents (Claude, Goose, Aider, Codex)
- Simple endpoints:
GET /messages- retrieves conversation historyPOST /message- sends a message to the agentGET /status- checks agent status ("stable" or "running")GET /events- SSE stream of agent events and updates
Installation Options
- Download binary from releases page
- Build from source:
go install github.com/coder/agentapi@latest
Web Interface
- Demo chat interface available at: https://coder.github.io/agentapi/chat
- Connects to your local AgentAPI server running on
localhost:3284
Distinguishing Features and Use Cases
AgentAPI differs from other AI coding tools by focusing on control rather than being an agent itself. When asked to compare it with claude-task-master, a project contributor clarified that while claude-task-master is more of a project manager, AgentAPI is a developer tool that enables controlling Claude Code or OpenAI Codex through HTTP calls instead of terminal commands.
This distinction is important as it positions AgentAPI as middleware that can power custom frontends, native desktop applications, or even enable one AI system to leverage the capabilities of another. The tool's simple API includes endpoints for retrieving conversation history, sending messages, checking agent status, and streaming events.
The project's long-term vision acknowledges that major agents may eventually release their own SDKs. If these vendors standardize on a common API, AgentAPI might become obsolete. However, if each maintains proprietary formats, AgentAPI aims to serve as a universal adapter, allowing developers to switch between agents without changing their code.
For developers looking to experiment with AI coding assistants or build custom integrations, AgentAPI represents a valuable addition to the toolkit, simplifying what would otherwise be a complex integration challenge.
Reference: AgentAPI