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alexsmirnov

MCP Server for continue.dev

by alexsmirnov

web_search

Search the web for information to enhance LLM interactions within the continue.dev environment by providing relevant data and resources.

Instructions

Search the web for information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Implementation Reference

  • Registers the web_search tool with the MCP server using the @tool decorator.
    @self.mcp.tool(name="web_search", description="Search the web for information")
  • The handler function for the web_search tool. It performs some root listing logging and delegates the search to perplexity_search.do_search.
    async def web_search(query: str) -> str: """ Performs a web search using the provided query. Find the most relevant pages and return summary result. Args: query: The search query. Returns: The summary of the most relevant search results. """ try: session: ServerSession = self.mcp.get_context().session if session.check_client_capability(ClientCapabilities(roots=RootsCapability())) : result = await session.list_roots() logger.info(f"Result: {result}") for root in result.roots: logger.info(f"Root: {root.name} , location: {root.uri}") else: logger.info("Client does not support roots capability") # Try to get the roots from the environment variable ROOT root_value = os.getenv("ROOT") logger.info(f"ROOT environment variable: {root_value}") except Exception as e: logger.error(f"Error listing roots: {e}") return await perplexity_search.do_search(query, self.config)
  • Core helper function that performs the actual web search using Perplexity AI API.
    async def do_search(query: str, config: ServerConfig) -> str: """ Performs a search and returns the results. Args: query: The search query. Returns: The search query string back. """ url = "https://api.perplexity.ai/chat/completions" headers = { "Authorization": f"Bearer {config.perplexity_api_key}", "Content-Type": "application/json" } payload = { "model": "sonar", "messages": [ {"role": "system", "content": "Be precise and concise."}, {"role": "user", "content": query} ], "max_tokens": 1000, "temperature": 0.01, "top_p": 0.9, "return_related_questions": False, "web_search_options": { "search_context_size": "medium" } } async with httpx.AsyncClient() as client: response = await client.post(url, json=payload, headers=headers) response.raise_for_status() return format_response_with_citations(response.json())
  • Helper function to format the Perplexity API response with citations in markdown.
    def format_response_with_citations(response: dict) -> str: """ Formats the response from Perplexity.ai to include citations as a markdown list. Args: response: The JSON response from Perplexity.ai. Returns: A formatted string with the content and citations. """ content = response.get("choices", [{}])[0].get("message", {}).get("content", "No content available") citations = response.get("citations", []) if citations: citations_md = "\n".join([f"- {url}" for url in citations]) return f"{content}\n\n### Citations\n{citations_md}" return content
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