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\nš 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 `ā 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 `ā 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 = `ā ļø 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"), }, },