c29b9e1ba9
CT 144 (certus-workbrain) restored to 10.30.20.249 All configs updated: MCP proxy, backend, BTCPay webhook
82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
#!/usr/bin/env python3
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"""AI Research Engine — Thin MCP Proxy. Admin key for backend auth."""
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import json
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import httpx
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from mcp.server import FastMCP
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BACKEND_URL = "http://10.30.20.250:8000"
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ADMIN_KEY = "sk-admin-unlimited-2026"
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client = httpx.Client(timeout=120.0)
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def _get(path: str) -> dict:
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sep = "&" if "?" in path else "?"
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r = client.get(f"{BACKEND_URL}{path}{sep}api_key={ADMIN_KEY}")
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r.raise_for_status()
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return r.json()
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mcp = FastMCP("ai-research-engine", instructions="AI Research Engine — private knowledge acquisition. 10 tools.")
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@mcp.tool()
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def search_web(query: str, category: str = "", limit: int = 10) -> str:
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"""Full-text search across indexed documents."""
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r = _get(f"/api/search?q={query}&category={category}&limit={limit}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def semantic_search(query: str, limit: int = 10) -> str:
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"""Search by meaning using vector embeddings."""
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r = _get(f"/api/semantic-search?q={query}&limit={limit}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def crawl_url(url: str, depth: int = 1) -> str:
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"""Crawl a URL and index it."""
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r = _get(f"/api/crawl?url={url}&depth={depth}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def crawl_topic(topic: str, max_urls: int = 20) -> str:
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"""Discover and crawl sources for a topic."""
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r = _get(f"/api/crawl-topic?topic={topic}&max_urls={max_urls}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def research_topic(topic: str) -> str:
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"""Full pipeline: search → crawl → AI summary."""
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r = _get(f"/api/research?topic={topic}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def retrieve_document(url: str) -> str:
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"""Get full indexed content of a document."""
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r = _get(f"/api/document?url={url}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def summarize_sources(urls: str, instruction: str = "Summarize key points") -> str:
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"""AI summary of multiple URLs. urls: comma-separated."""
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r = _get(f"/api/summarize?urls={urls}&instruction={instruction}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def extract_information(url: str, schema: str = "company names, products, prices") -> str:
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"""Extract structured data from a document using LLM."""
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r = _get(f"/api/extract?url={url}&schema={schema}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def create_report(topic: str, sources: str = "") -> str:
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"""Generate comprehensive research report."""
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r = _get(f"/api/report?topic={topic}&sources={sources}")
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return json.dumps(r, indent=2)
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@mcp.tool()
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def index_status() -> str:
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"""System health + business stats."""
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r = _get("/api/status")
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return json.dumps(r, indent=2)
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if __name__ == "__main__":
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mcp.run(transport="stdio")
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