ai-agent-gateway 0.1.0

Generic Claude agent gateway with MCP tool support and streaming

claude-gateway

A Python package for building streaming Claude agent applications with MCP (Model Context Protocol) tool support. Handles the agent loop, tool dispatch, MCP server management, and SSE event streaming — so you can focus on your domain logic.

Install

pip install claude-gateway

Quick Start

import asyncio
from claude_gateway import AgentRunner, EventLog, McpClientManager, ToolDispatcher

async def main():
    # 1. Set up MCP client (reads ~/.claude.json for server configs)
    mcp = McpClientManager(
        allowed_servers={"my-mcp-server"},
        builtin_tool_names=set(),
    )
    await mcp.startup()

    # 2. Create a tool dispatcher with local handlers + MCP tools
    async def my_tool(tool_input, *, call_index=0):
        return {"result": f"Hello from {tool_input.get('name', 'world')}"}, None

    dispatcher = ToolDispatcher(
        mcp_client=mcp,
        local_tool_handlers={"greet": my_tool},
    )

    # 3. Create event log for SSE streaming
    event_log = EventLog(session_id="session-001")

    # 4. Run the agent
    runner = AgentRunner(
        event_log=event_log,
        dispatcher=dispatcher,
        session_id="session-001",
        auth_config={"auth_mode": "api", "api_key": "sk-ant-..."},
        mcp_client=mcp,
        get_tool_definitions=lambda: [
            {"name": "greet", "description": "Greet someone", "input_schema": {
                "type": "object",
                "properties": {"name": {"type": "string"}},
            }},
            *mcp.get_tool_definitions(),
        ],
    )

    # Start streaming (non-blocking, populates event_log)
    asyncio.create_task(runner.run(
        messages=[{"role": "user", "content": "Say hello"}],
        system_prompt="You are a helpful assistant.",
    ))

    # Consume SSE events
    async for entry in event_log.iter_from():
        print(entry.event)
        if entry.event.get("type") == "stream_complete":
            break

    await mcp.shutdown()

asyncio.run(main())

API Reference

AgentRunner

Core streaming agent loop. Sends messages to Claude, processes tool calls, and emits SSE events.

• Hooks: on_tool_result, on_usage, on_tool_timing — async callbacks for observability
• Sub-agents: sub_agent_config + spawn_sub_agent() for parallel task delegation
• Streaming: Emits thinking_delta, text_delta, tool_use, tool_result, stream_complete events

ToolDispatcher

Routes tool calls to local handlers or MCP servers. Supports approval gates for sensitive operations.

• local_tool_handlers: Dict[str, handler] — local async functions
• needs_approval / request_approval: Optional approval flow for gated tools
• approved_tool_types: Session-persistent set of pre-approved tools

McpClientManager

Manages MCP server connections via stdio. Reads server configs from ~/.claude.json.

• allowed_servers: Whitelist of server names to connect
• builtin_tool_names: Tool names to skip (avoids collisions with local tools)
• timeout_overrides: Per-server call timeouts

EventLog

Async event stream for SSE. Append events, iterate from any sequence number.

• append(event) — add an event
• iter_from(after_seq) — async iterator, blocks until new events arrive
• close() — emit terminal event and seal the log

Supporting Types

• ToolResult = Tuple[Optional[Any], Optional[Dict[str, Any]]] — (result, error) pair
• ApprovalRequest / ApprovalDecision — approval flow dataclasses
• SubAgentConfig — excluded tools, system prompt, max turns for sub-agents
• ToolResultContext — full context passed to on_tool_result hook
• LogEntry — sequence number, timestamp, event dict

License

MIT