aibridge

aibridge is an HTTP gateway that sits between AI clients and upstream AI providers (Anthropic, OpenAI). It intercepts requests to record token usage, prompts, and tool invocations per user. Optionally supports centralized MCP tool injection with allowlist/denylist filtering.

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.Handler that 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

1. Client sends request to /anthropic/v1/messages or /openai/v1/chat/completions
2. Actor extraction: Request must have an actor in context (via AsActor()).
3. Upstream call: Request forwarded to the AI provider
4. Response relay: Response streamed/sent to client
5. 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
tokens_total	Counter	Token usage (input/output)
prompts_total	Counter	User prompt count
injected_tool_invocations_total	Counter	MCP tool invocations
passthrough_total	Counter	Non-intercepted requests

Recorder Interface

Implement Recorder to persist usage data to your database. The example uses SQLite (example/recorder.go):

• aibridge_interceptions - request metadata (provider, model, initiator, timestamps)
• aibridge_token_usages - input/output token counts per response
• aibridge_user_prompts - user prompts
• aibridge_tool_usages - tool invocations (injected and client-defined)

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
}

Example

See example/ for a complete runnable example with SQLite persistence and DeepWiki MCP integration.

Setup

1. Get API keys from the provider consoles:

   • Anthropic: https://console.anthropic.com/settings/keys
   • OpenAI: https://platform.openai.com/api-keys

2. Set environment variables:

   export ANTHROPIC_API_KEY="sk-ant-..."
   export OPENAI_API_KEY="sk-..."

3. Run the example:

   cd example && go run .

4. Test with curl:

   curl -X POST http://localhost:8080/anthropic/v1/messages \
     -H "Content-Type: application/json" \
     -d '{
       "model": "claude-sonnet-4-20250514",
       "max_tokens": 1024,
       "messages": [{"role": "user", "content": "Hello!"}],
       "stream": true
     }'

5. Test with Claude Code: Claude Code allows a base URL override via ANTHROPIC_BASE_URL.

   

Supported Routes

Provider	Route	Type
Anthropic	/anthropic/v1/messages	Bridged (intercepted)
Anthropic	/anthropic/v1/models	Passthrough
Anthropic	/anthropic/v1/messages/count_tokens	Passthrough
OpenAI	/openai/v1/chat/completions	Bridged (intercepted)
OpenAI	/openai/v1/models	Passthrough