claude

@ageflow/runner-claude

Claude CLI runner for ageflow. Spawns the claude CLI as a subprocess and parses its JSON output.

Install

bun add @ageflow/runner-claude

Requires the Claude CLI to be installed and authenticated:

npm install -g @anthropic-ai/claude-code
claude --version  # verify

Usage

import { registerRunner } from "@ageflow/core";
import { ClaudeRunner } from "@ageflow/runner-claude";

registerRunner("claude", new ClaudeRunner());

Then use runner: "claude" in any defineAgent call:

const myAgent = defineAgent({
  runner: "claude",
  model: "claude-sonnet-4-6",   // or "claude-opus-4-6", "claude-haiku-4-5"
  input: z.object({ prompt: z.string() }),
  output: z.object({ result: z.string() }),
  prompt: ({ prompt }) => prompt,
});

Features

• Session continuity — when an agent uses sessionToken, the runner passes --resume <session_id> to the CLI, preserving conversation context across calls
• HITL detection — if Claude requests a tool the workflow hasn't approved, the runner surfaces a HITLRequest instead of throwing
• Automatic retries — handled by the executor; the runner itself is stateless per call
• JSON output — parses Claude's --output-format json JSONL stream, extracts the result line

Supported models

Any model supported by your claude CLI version. Common values:

Model	ID
Claude Sonnet 4.6	claude-sonnet-4-6
Claude Opus 4.6	claude-opus-4-6
Claude Haiku 4.5	claude-haiku-4-5

Using MCP servers

Pass MCP server configuration via mcp.servers on any defineAgent call. The Claude runner passes --mcp-config with inline JSON and --strict-mcp-config to the Claude CLI — no external config file is required.

import { defineAgent, safePath } from "@ageflow/core";
import { z } from "zod";

const fileAgent = defineAgent({
  runner: "claude",
  model: "claude-sonnet-4-6",
  input: z.object({ query: z.string() }),
  output: z.object({ result: z.string() }),
  prompt: ({ query }) => query,
  mcp: {
    servers: [
      {
        name: "filesystem",
        command: "npx",
        args: ["-y", "@modelcontextprotocol/server-filesystem", "/workspace"],
        // Allowlist — only these tools are exposed to the model
        tools: ["read_file", "list_directory"],
        // Refine — validate path args before forwarding to the server
        refine: {
          read_file: z.object({ path: safePath({ allowAbsolute: false }) }),
        },
        // ${env:VAR} is resolved at launch time by the executor
        env: { NODE_ENV: "${env:NODE_ENV}" },
      },
    ],
  },
});

Allowlist (tools): when set, only the listed tools are passed to the CLI via --allowedTools mcp__filesystem__read_file flag (comma-joined). Unlisted tools are denied before they reach the model.

Refine (refine): a map of tool name → Zod schema. Arguments are validated against the schema before the call is dispatched. Use safePath() to prevent path traversal.

Environment expansion (env): values of the form ${env:VAR} are replaced with the corresponding process environment variable at launch time.

License

MIT