Codex sends the results of custom (freeform) tools such as `apply_patch` back as `custom_tool_call_output` input items. `RequestPayload.correlatingToolCallID` only matched `function_call_output`, so these follow-up interceptions had no correlating tool call ID. They were not linked to the interception that issued the tool call, which left blank AI Gateway sessions. [Example session](https://dogfood.cdr.dev/ai-gateway/sessions/01a1184a-08a4-7d50-8e15-a12368302a2f) <img width="996" height="576" alt="image" src="https://github.com/user-attachments/assets/5bce6035-963b-4438-897b-bee36ead5a47" /> `custom_tool_call_output` is now handled the same way as `function_call_output`. The earlier `custom_tool_call` is already recorded as a tool usage with its `call_id`, and `GetAIBridgeInterceptionLineageByToolCallID` does not check the tool type, so lineage now resolves without any other change. Fixes AIGOV-707 <details> <summary>Implementation notes</summary> - **Reproduction first:** the first commit adds blocking and streaming `custom_tool_result.txtar` fixtures. Each one is a follow-up turn that replays a `custom_tool_call` and ends with its `custom_tool_call_output`. `TestResponsesOutputMatchesUpstream` now checks `CorrelatingToolCallID` on every case, and `TestCorrelatingToolCallID` gains a `custom_tool_call_output` case plus a case where the last item is the tool call itself rather than its result. On that commit, both fixture cases and the unit case fail with `nil` instead of the custom tool's call ID. The second commit makes them pass. - **Out of scope:** other client-executed result types (`computer_call_output`, `shell_call_output`, `apply_patch_call_output`, `local_shell_call_output`) are not correlated either. Codex's `apply_patch` arrives as a custom tool, so it is covered here. Those other types were left out to keep this change tied to the reported bug. </details> > Generated by Coder Agents on behalf of @dannykopping.
aibridge
aibridge provides an HTTP handler that intercepts AI client requests bound for upstream AI providers (Anthropic, OpenAI, Copilot). It records token usage, prompts, and tool invocations per user. Optionally supports centralized MCP tool injection with allowlist/denylist filtering.
The handler is mounted by a host process. Today that host is coderd, which mounts the handler at /api/v2/ai-gateway/<provider>/*. Running aibridge as a separate process is planned for the future.
Architecture
┌─────────────────┐ ┌───────────────────────────────────────────┐
│ AI Client │ │ aibridge │
│ (Claude Code, │────▶│ ┌─────────────────┐ ┌─────────────┐ │
│ Cursor, etc.) │ │ │ RequestBridge │───▶│ Providers │ │
└─────────────────┘ │ │ (http.Handler) │ │ (Anthropic │ │
│ └─────────────────┘ │ OpenAI) │ │
│ └──────┬──────┘ │
│ │ │
│ ▼ │ ┌─────────────┐
│ ┌─────────────────┐ ┌─────────────┐ │ │ Upstream │
│ │ Recorder │◀───│ Interceptor │─── ───▶│ API │
│ │ (tokens, tools, │ │ (streaming/ │ │ │ (Anthropic │
│ │ prompts) │ │ blocking) │ │ │ OpenAI) │
│ └────────┬────────┘ └──────┬──────┘ │ └─────────────┘
│ │ │ │
│ ▼ ┌──────▼──────┐ │
│ ┌ ─ ─ ─ ─ ─ ─ ─ ┐ │ MCP Proxy │ │
│ │ Database │ │ (tools) │ │
│ └ ─ ─ ─ ─ ─ ─ ─ ┘ └─────────────┘ │
└───────────────────────────────────────────┘
Components
- RequestBridge: The main
http.Handlerthat routes requests to providers - Provider: Defines bridged routes (intercepted) and passthrough routes (proxied)
- Interceptor: Handles request/response processing and streaming
- Recorder: Interface for capturing usage data (tokens, prompts, tools)
- MCP Proxy (optional): Connects to MCP servers to list tool, inject them into requests, and invoke them in an inner agentic loop
Request Flow
- Client sends request to
/anthropic/v1/messagesor/openai/v1/chat/completions - Actor extraction: Request must have an actor in context (via
AsActor()). The host is responsible for authenticating the caller before invoking the handler. - Upstream call: Request forwarded to the AI provider
- Response relay: Response streamed/sent to client
- Recording: Token usage, prompts, and tool invocations recorded
With MCP enabled: Tools from configured MCP servers are centrally defined and injected into requests (prefixed bmcp_). Allowlist/denylist regex patterns control which tools are available. When the model selects an injected tool, the gateway invokes it in an inner agentic loop, and continues the conversation loop until complete.
Passthrough routes (/v1/models, /v1/messages/count_tokens) are reverse-proxied directly.
Observability
Prometheus Metrics
Create metrics with NewMetrics(prometheus.Registerer):
| Metric | Type | Description |
|---|---|---|
interceptions_total |
Counter | Intercepted request count |
interceptions_inflight |
Gauge | Currently processing requests |
interceptions_duration_seconds |
Histogram | Request duration |
passthrough_total |
Counter | Non-intercepted requests forwarded to the upstream |
prompts_total |
Counter | User prompt count |
tokens_total |
Counter | Token usage (input, output, cache read/write, provider extras) |
injected_tool_invocations_total |
Counter | Injected MCP tool invocations performed by the handler |
non_injected_tool_selections_total |
Counter | Client-defined tool selections returned by the model |
circuit_breaker_state |
Gauge | Circuit breaker state per provider/endpoint (0=closed, 0.5=half, 1=open) |
circuit_breaker_trips_total |
Counter | Times the circuit breaker transitioned to open |
circuit_breaker_rejects_total |
Counter | Requests rejected due to an open circuit breaker |
Recorder Interface
Implement Recorder to persist usage data to your database:
aibridge_interceptions- request metadata (provider, model, initiator, timestamps)aibridge_token_usages- input/output and cache read/write token counts per responseaibridge_user_prompts- user promptsaibridge_tool_usages- tool invocations (injected and client-defined)aibridge_model_thoughts- model reasoning content (thinking, reasoning summaries, commentary)
type Recorder interface {
RecordInterception(ctx context.Context, req *InterceptionRecord) error
RecordInterceptionEnded(ctx context.Context, req *InterceptionRecordEnded) error
RecordTokenUsage(ctx context.Context, req *TokenUsageRecord) error
RecordPromptUsage(ctx context.Context, req *PromptUsageRecord) error
RecordToolUsage(ctx context.Context, req *ToolUsageRecord) error
RecordModelThought(ctx context.Context, req *ModelThoughtRecord) error
}
Supported Routes
Each provider instance is mounted under /api/v2/ai-gateway/<name>, where <name> is the provider's configured name. For example, with an Anthropic provider named my-anthropic, its /messages endpoint would be reachable at /api/v2/ai-gateway/my-anthropic/v1/messages.
If a name is not set, the route path defaults to the provider's type: anthropic, openai, or copilot. The table below uses the default names.
(/*) denotes a route that handles both the exact path and any subpaths. A trailing /* denotes subpaths only.
| Provider | Route | Type |
|---|---|---|
| Anthropic | /anthropic/v1/messages |
Bridged (intercepted) |
| Anthropic | /anthropic/v1/messages/count_tokens |
Passthrough |
| Anthropic | /anthropic/v1/models(/*) |
Passthrough |
| Anthropic | /anthropic/api/event_logging/* |
Passthrough |
| OpenAI | /openai/v1/chat/completions |
Bridged (intercepted) |
| OpenAI | /openai/v1/responses |
Bridged (intercepted) |
| OpenAI | /openai/v1/responses/* |
Passthrough |
| OpenAI | /openai/v1/conversations(/*) |
Passthrough |
| OpenAI | /openai/v1/models(/*) |
Passthrough |
| Copilot | /copilot/chat/completions |
Bridged (intercepted) |
| Copilot | /copilot/responses |
Bridged (intercepted) |
| Copilot | /copilot/models(/*) |
Passthrough |
| Copilot | /copilot/agents/* |
Passthrough |
| Copilot | /copilot/mcp/* |
Passthrough |
| Copilot | /copilot/.well-known/* |
Passthrough |