agentbridge-cli 0.1.18

🌉 Claude, Codex, and OpenRouter through one API 🔌

AgentBridge is a local API server that lets developers use Claude Code, Codex, and OpenRouter in chat apps built for OpenAI. Run it from the command line or the macOS menu-bar app, connect your chat client, and choose a backend with a provider-prefixed model ID.

It supports streaming and non-streaming responses, image and PDF inputs where the backend accepts them, native Codex image editing, strict JSON Schema output, OpenAI-style tool calls, a live dashboard, and local JSON session logs.

Legal notice: agentbridge can use Claude Code SDK and Codex CLI access through your local subscriptions, and can forward requests to OpenRouter when configured. You are responsible for determining whether your use complies with each service's terms. Use it conservatively and at your own risk.

Install

Command line

Requires Python 3.12+ and uv:

uv tool install agentbridge-cli
agentbridge

If you installed an earlier release under the previous PyPI distribution name, migrate once with:

uv tool uninstall agentbridge-py
uv tool install agentbridge-cli

The Python import and executable remain agentbridge.

Open the dashboard, try the built-in chat, or use http://localhost:8082/api/v1 as an OpenAI-compatible base URL.

Before sending requests, install Claude Code or Codex CLI for the backend you use. Authenticate in another terminal if AgentBridge is already running:

claude auth login  # for claudecode/* models
codex login        # for codex/* models

For OpenRouter, start agentbridge once and add OPENROUTER_API_KEY to ~/.config/agentbridge/.env.

macOS menu-bar app

On an Apple silicon Mac running macOS 13+, download the arm64 DMG from the latest release, drag AgentBridge.app to Applications, and open it. The app is ad-hoc signed and not Apple-notarized; macOS may require you to Control-click the app, choose Open, and confirm on first launch. Intel Macs are not supported.

The menu-bar window starts and stops the server, shows health and activity, opens the dashboard, and configures the port, worker count, and launch at login. It bundles Python 3.12 and AgentBridge dependencies. Install and authenticate provider tools separately as above; configuration and logs stay under ~/.config/agentbridge/.

From source

git clone https://github.com/tsilva/agentbridge.git
cd agentbridge
uv sync --frozen --extra test
uv run agentbridge

To build the macOS app from the same checkout, install the Xcode Command Line Tools and run:

scripts/build_macos_app.sh
open build/macos/arm64/AgentBridge-*.dmg

This requires an Apple silicon Mac running macOS 13+ and no Apple Developer account. See macOS development instructions for details.

Usage

curl http://localhost:8082/api/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"claudecode/sonnet","messages":[{"role":"user","content":"Hello!"}]}'

Every request requires a model with one of these provider namespaces:

The dashboard chat defaults to codex/gpt-6.1-sol; a previously selected model is restored when returning to an existing chat. Monitor error cards use Refresh to reload saved request details; chat error cards use Retry to resend the failed request, including after navigating away or reloading. Chat drafts are preserved within the browser session. Enter sends a message; Shift+Enter or Alt+Enter inserts a newline. Interrupted streams are recorded as cancelled requests in Monitor, and Codex subprocesses are stopped. Incomplete or malformed response streams show a retryable error and leave chat history unchanged.

Codex chat defaults to low reasoning effort for gpt-6-astra and high for gpt-6.1-sol, gpt-5.6-sol, and gpt-5.5; requests can override this. Astra image generation also uses low reasoning effort.

With the OpenAI Python SDK installed, connect using any placeholder API key:

from openai import OpenAI

client = OpenAI(base_url="http://localhost:8082/api/v1", api_key="not-needed")
response = client.chat.completions.create(
    model="codex/gpt-6-astra",
    reasoning_effort="high",
    messages=[{"role": "user", "content": "Hello from Codex!"}],
)
print(response.choices[0].message.content)

Codex can also edit one PNG, JPEG, or WebP reference through the image route. The request returns one base64-encoded image without saving session logs. Run this example from a repository checkout using the included sample image:

PAGE_DATA="$(base64 < tests/fixtures/ocr_test_document.png | tr -d '\n')"
curl http://localhost:8082/api/v1/images \
  -H "Content-Type: application/json" \
  -d "{\"model\":\"codex/gpt-6-astra\",\"prompt\":\"Make this look like a scanner capture without changing any content.\",\"input_references\":[{\"type\":\"image_url\",\"image_url\":{\"url\":\"data:image/png;base64,$PAGE_DATA\"}}],\"n\":1,\"store\":false}"

GET /api/v1/capabilities reports whether the local Codex CLI is available, authenticated, and supports the strict image and JSON-schema profiles.

Commands

agentbridge                                             # start on 127.0.0.1:8082
agentbridge --port 8083                                  # choose another port
agentbridge --workers 3                                  # set Claude pool and Codex concurrency to 3
agentbridge --version                                    # print package and git version
uv run --frozen --extra test pytest -q                    # run tests
uv run --frozen --extra test ruff check agentbridge tests  # lint Python
swift test --package-path macos                          # test the macOS app
scripts/build_macos_app.sh                               # build a local signed app and DMG
uv lock --check                                         # verify the lockfile
uv build                                                # build wheel and source distribution

Notes

• The server listens on 127.0.0.1:8082 by default and accepts any placeholder client API key.
• Public routes include POST /api/v1/chat/completions, POST /api/v1/images, GET /api/v1/models, GET /api/v1/capabilities, GET /health, /dashboard, and /dashboard/chat.
• Monitor live text uses GET /dashboard/stream/{request_id}. Its optional offset counts already-rendered characters; buffered text after that offset is replayed before new chunks.
• GET /health includes safe operator status used by the menu-bar app: version, start time, uptime, configured workers, active requests, and pool state when initialized.
• Claude clients are created lazily, reused by model, and capped by the worker count. Claude sessions do not load filesystem settings and run with built-in tools disabled.
• Codex runs one ephemeral codex exec process per request in a temporary directory with read-only sandboxing, no approvals, and project rules ignored. Multimodal structured-output calls also ignore user config and disable execution and image-generation tools. Native image calls use the same strict profile, keep execution disabled, and enable the image-generation capability needed for the edit.
• Claude and Codex function calls are represented through prompted JSON; OpenRouter tool calls pass through its SDK. Session logs and extracted image or PDF attachments are saved under ~/.config/agentbridge/logs/sessions by default.
• Streaming provider failures emit an OpenAI-shaped error object as an SSE data event before [DONE]; they are not returned as assistant message text.
• Set store: false on chat requests to suppress session-log artifacts. The native image route requires store: false, accepts data URLs only, validates both rasters, locates the result from the structured Codex thread ID, and removes that thread's generated-image directory after the request.

Configuration lives in ~/.config/agentbridge/.env. Process environment variables take precedence. CLI flags override the configured port and worker count.

Publishing

Releases use the Release GitHub Actions workflow and PyPI Trusted Publishing for the agentbridge-cli project. The publisher is scoped to owner tsilva, repository agentbridge, workflow release.yml, and environment pypi; no PyPI API token is required. GitHub Releases contain the Python distributions plus an ad-hoc-signed arm64 macOS DMG and SHA-256 checksum. The DMG is not Apple-notarized and requires no Apple Developer credentials. Release and validation builds run in GitHub Actions, including Python package audits and macOS application checks. $build-release prepares version metadata locally and monitors Actions; it does not require a local application build. A manual dispatch with publish=false and attach_macos=false builds both artifact sets without publishing them. Releases through 0.1.10 remain available under the previous agentbridge-py distribution name.

Architecture

License

MIT