92 lines
2.5 KiB
Python
92 lines
2.5 KiB
Python
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"""MCP server for the web researcher.
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Exposes a single tool `research` that delegates to WebResearcher.
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Run with: python -m researchers.web.server
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"""
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import asyncio
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import os
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import sys
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from typing import Optional
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from mcp.server.fastmcp import FastMCP
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from researchers.web.agent import WebResearcher
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from researchers.web.models import ResearchConstraints
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mcp = FastMCP(
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name="marchwarden-web-researcher",
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instructions=(
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"A Marchwarden web research specialist. "
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"Call the research tool with a question to get a grounded, "
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"evidence-based answer with citations, gaps, open questions, "
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"and confidence scoring."
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),
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)
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def _read_secret(key: str) -> str:
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"""Read a secret from ~/secrets file."""
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secrets_path = os.path.expanduser("~/secrets")
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with open(secrets_path) as f:
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for line in f:
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if line.startswith(f"{key}="):
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return line.split("=", 1)[1].strip()
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raise ValueError(f"Key {key} not found in {secrets_path}")
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def _get_researcher() -> WebResearcher:
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"""Create a WebResearcher with keys from ~/secrets."""
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return WebResearcher(
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anthropic_api_key=_read_secret("ANTHROPIC_API_KEY"),
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tavily_api_key=_read_secret("TAVILY_API_KEY"),
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model_id=os.environ.get("MARCHWARDEN_MODEL", "claude-sonnet-4-5-20250514"),
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)
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@mcp.tool()
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async def research(
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question: str,
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context: Optional[str] = None,
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depth: str = "balanced",
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max_iterations: int = 5,
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token_budget: int = 20000,
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) -> str:
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"""Research a question using web search and return a structured answer.
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Args:
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question: The question to investigate.
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context: What the caller already knows (optional).
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depth: Research depth — "shallow", "balanced", or "deep".
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max_iterations: Maximum number of search/fetch iterations (1-20).
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token_budget: Maximum tokens to spend (1000-100000).
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Returns:
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JSON string containing the full ResearchResult with answer,
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citations, gaps, discovery_events, open_questions, confidence,
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and cost_metadata.
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"""
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researcher = _get_researcher()
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constraints = ResearchConstraints(
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max_iterations=max_iterations,
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token_budget=token_budget,
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)
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result = await researcher.research(
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question=question,
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context=context,
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depth=depth,
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constraints=constraints,
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)
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return result.model_dump_json(indent=2)
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def main():
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"""Run the MCP server on stdio."""
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mcp.run(transport="stdio")
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if __name__ == "__main__":
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main()
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