start_context_engine

Initialize the context engine to access current library documentation and code examples for AI coding assistance.

Instructions

Starts the context engine and returns a confirmation message.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`projectRoot`	Yes	The project root directory

Implementation Reference

src/lib/api.ts:91-155 (handler)

Core implementation of the startContextEngine function, which handles local documentation setup and remote API call to start the context engine.

export async function startContextEngine(
  projectRoot: string,
  clientIp?: string,
  apiKey?: string,
  serverUrl?: string
): Promise<string> {
  if (!projectRoot) {
    throw new Error("Project root directory is required for context engine initialization");
  }

  let apiResponse = "";
  let documentationStatus = "";

  try {
    // Step 1: Setup local documentation structure first
    logger.info("Setting up local documentation structure");
    const setupResult = await setupDocumentationStructure(projectRoot);

    if (setupResult.success) {
      documentationStatus = `\n\n📁 Local Documentation Structure: ${setupResult.message}`;
      logger.info("Local documentation structure setup completed", {
        status: setupResult.status as unknown as Record<string, unknown>,
      });
    } else {
      logger.warn("Local documentation structure setup failed", {
        status: setupResult.status as unknown as Record<string, unknown>,
      });
      // Don't proceed with API call if local setup fails
      return `❌ Failed to setup local documentation structure: ${setupResult.message}`;
    }
  } catch (error) {
    logger.error("Local documentation structure setup failed", {
      error: error instanceof Error ? error.message : String(error),
    });
    // Don't proceed with API call if local setup fails
    return `❌ Failed to setup local documentation structure: ${error instanceof Error ? error.message : String(error)}`;
  }

  try {
    // Step 2: Start the context engine via API (only if local setup succeeded)
    logger.info("Starting ContextEngine via API");
    const url = buildApiUrl("start-context-engine", {}, serverUrl);
    const headers = generateHeaders(clientIp, apiKey, { "X-ContextEngine-Source": "mcp-server" });

    const response = await makeApiRequest(url, headers, "start context engine");
    const text = await response.text();

    if (!text || text === "No content available") {
      apiResponse = "Context engine start request sent but no confirmation available.";
    } else {
      apiResponse = text;
    }

    logger.info("ContextEngine API call successful");
  } catch (error) {
    logger.error("ContextEngine API call failed", {
      error: error instanceof Error ? error.message : String(error),
    });

    apiResponse = `⚠️  ContextEngine API call failed: ${error instanceof Error ? error.message : String(error)}`;
  }
  
  // Return combined response
  return `${apiResponse}${documentationStatus}`;
}

src/index.ts:77-107 (registration)

MCP tool registration for 'start_context_engine', including input schema, description, and handler that delegates to the core startContextEngine function.

server.registerTool(
  "start_context_engine",
  {
    title: "Start Context Engine",
    description: "Starts the context engine and returns a confirmation message.",
    inputSchema: {
      projectRoot: z.string().describe("The project root directory"),
    },
  },
  async (args) => {
    // Validate API key based on environment
    validateApiKey(apiKey, finalServerUrl);

    const startContextEngineResponse = await startContextEngine(
      args.projectRoot,
      clientIp,
      apiKey,
      finalServerUrl
    );

    return {
      content: [
        {
          type: "text",
          text: startContextEngineResponse,
        },
      ],
    };
  }
);

src/index.ts:80-86 (schema)

Input schema definition for the tool using Zod, requiring projectRoot string.

{
  title: "Start Context Engine",
  description: "Starts the context engine and returns a confirmation message.",
  inputSchema: {
    projectRoot: z.string().describe("The project root directory"),
  },
},

ContextEngine MCP Server