mcp

(* An agent with access to a document workspace via MCP.
   Demonstrates HTTP transport with bearer token authentication.

   Run:
     LDC_TOKEN=<your-token> plumb examples/mcp/mcp.plumb

   Or interactively:
     LDC_TOKEN=<your-token> chat examples/mcp/mcp.plumb

   Then ask:
     "Search for documents about compaction"
     "Read the file notes/observations/OBS-005.md"
     "What documents are in the workspace?" *)

let ldc = {
  url: "https://leithdocs.com/ldc/mcp",
  token_env: "LDC_TOKEN",
  tools: ["read", "search", "grep"]
}

let assistant : !string -> !string = agent {
  provider: "anthropic",
  model: "claude-haiku-4-5",
  prompt: "You are a research assistant with access to a document workspace via MCP tools. Use the available tools to find and read documents. Respond with a brief summary of what you found.",
  mcp: [ldc],
  runtime_context: true
}

let main : !string -> !string = plumb(input, output) {
  spawn assistant(input, output)
}

"""MCP document workspace query.

Sends a query to an agent that has access to a document workspace
via MCP tools (read, search, grep).

Requires: ANTHROPIC_API_KEY, LDC_TOKEN

Usage:
    ANTHROPIC_API_KEY=sk-... LDC_TOKEN=... python mcp.py
"""

import os
from pathlib import Path

import plumbing as pb

spec = Path(__file__).parent / "mcp.plumb"
query = "Search for documents about compaction"

results = pb.call_sync(
    spec,
    query,
    auto_approve=True,
    env={"LDC_TOKEN": os.environ.get("LDC_TOKEN", "")},
)
for result in results:
    print(result)