LinkedIn MCP Assistant

Instructions

Implementation Reference

• cli.js:424-511 (handler)

  Handler implementation for the 'analyze_linkedin_chat' tool. Validates 'query' (required string) and 'conversation_history' (optional array of messages), proxies the request to the backend API endpoint, and returns the reply text or an error message.
  } else if (name === 'analyze_linkedin_chat') { console.error(`${packageName}: Received call for analyze_linkedin_chat tool.`); const apiKey = process.env.LINKEDIN_MCP_API_KEY; const query = args?.query; const conversationHistory = args?.conversation_history || []; if (!apiKey) { sendResponse({ jsonrpc: "2.0", error: { code: -32001, message: "Server Configuration Error: API Key not set." }, id }); return; } if (typeof query !== 'string' || query.trim() === '') { sendResponse({ jsonrpc: "2.0", error: { code: -32602, message: "Invalid arguments: 'query' (string) required." }, id }); return; } if (!Array.isArray(conversationHistory)) { sendResponse({ jsonrpc: "2.0", error: { code: -32602, message: "Invalid arguments: 'conversation_history' must be an array." }, id }); return; } try { const headers = { "Authorization": `Bearer ${apiKey}`, "Content-Type": "application/json", "Accept": "application/json" }; const payload = { "query": query, "conversation_history": conversationHistory }; console.error(`${packageName}: Calling analyze chat API: ${backendAnalyzeChatApiUrl} with payload:`, JSON.stringify(payload, null, 2)); const apiResponse = await axios.post(backendAnalyzeChatApiUrl, payload, { headers, timeout: 60000 }); console.error(`${packageName}: Analyze chat API response status: ${apiResponse.status}`); console.error(`${packageName}: Analyze chat API response data:`, JSON.stringify(apiResponse.data, null, 2)); if (apiResponse.data && apiResponse.data.reply) { sendResponse({ jsonrpc: "2.0", result: { content: [ { type: "text", text: apiResponse.data.reply } ], isError: false }, id }); } else { const errorMessage = apiResponse.data?.error || "Backend API Error (no detail)"; console.error(`${packageName}: Analyze chat API Error: ${errorMessage}`); sendResponse({ jsonrpc: "2.0", result: { content: [ { type: "text", text: `Failed to analyze LinkedIn chat: ${errorMessage}` } ], isError: true }, id }); } } catch (error) { let errorMessage = `Failed to call analyze chat API: ${error.message}`; if (error.response) { // Extract the error message directly from the backend response const backendError = error.response.data?.error || error.response.data?.message; errorMessage = backendError || `Backend API Error (Status ${error.response.status})`; console.error(`${packageName}: Analyze chat API Error Response:`, error.response.data); } else if (error.request) { errorMessage = "No response received from analyze chat API."; } console.error(`${packageName}: ${errorMessage}`); sendResponse({ jsonrpc: "2.0", result: { content: [ { type: "text", text: `Failed to analyze LinkedIn chat: ${errorMessage}` } ], isError: true }, id }); }
• cli.js:1271-1301 (schema)

  Input schema definition for the 'analyze_linkedin_chat' tool, defining the expected parameters: required 'query' string and optional 'conversation_history' array of role/content objects.
  name: "analyze_linkedin_chat", description: "Ask questions about the user's LinkedIn profile, content, or network, with support for multi-turn conversations.", inputSchema: { type: "object", properties: { query: { type: "string", description: "The question or request about LinkedIn data to be analyzed." }, conversation_history: { type: "array", description: "Optional. Previous messages in the conversation for context. Each message must have 'role' (user/assistant) and 'content' (text).", items: { type: "object", properties: { role: { type: "string", description: "The sender of the message: 'user' or 'assistant'." }, content: { type: "string", description: "The text content of the message." } }, required: ["role", "content"] } } }, required: ["query"] } },
• cli.js:1181-1373 (registration)

  The tool is registered by being included in the 'tools/list' response, which lists all available tools with their schemas.
  if (method === 'tools/list') { console.error(`${packageName}: Received tools/list request, sending known tool.`); sendResponse({ jsonrpc: "2.0", id: id, result: { tools: [ { name: "publish_linkedin_post", description: "Publish a text post to LinkedIn, optionally including media (images/videos) specified by URL.", inputSchema: { type: "object", properties: { post_text: { type: "string", description: "The text content of the LinkedIn post." }, media: { type: "array", description: "Optional. A list of media items to attach to the post. Each item must have a 'file_url' pointing to a direct image or video URL and a 'filename'.", items: { type: "object", properties: { file_url: { type: "string", description: "A direct URL to the image or video file (e.g., ending in .jpg, .png, .mp4)." }, filename: { type: "string", description: "A filename for the media item (e.g., 'promo_video.mp4')." } }, required: ["file_url", "filename"] } } }, required: ["post_text"] } }, { name: "schedule_linkedin_post", description: "Schedule a text post for LinkedIn at a specific future date and time, optionally including media (images/videos) specified by URL.", inputSchema: { type: "object", properties: { post_text: { type: "string", description: "The text content of the LinkedIn post to be scheduled." }, scheduled_date: { type: "string", description: "The date and time to publish the post, in ISO 8601 format (e.g., '2025-12-31T10:00:00Z' or '2025-12-31T15:30:00+05:30'). Must be in the future." }, media: { type: "array", description: "Optional. A list of media items to attach to the post. Each item must have a 'file_url' pointing to a direct image or video URL and a 'filename'.", items: { type: "object", properties: { file_url: { type: "string", description: "A direct URL to the image or video file (e.g., ending in .jpg, .png, .mp4)." }, filename: { type: "string", description: "A filename for the media item (e.g., 'meeting_notes.mp4')." } }, required: ["file_url", "filename"] } } }, required: ["post_text", "scheduled_date"] } }, { name: "publish_twitter_post", description: "Publish a text post (tweet) to Twitter.", inputSchema: { type: "object", properties: { post_text: { type: "string", description: "The text content of the tweet (maximum 280 characters)." } }, required: ["post_text"] } }, { name: "analyze_linkedin_chat", description: "Ask questions about the user's LinkedIn profile, content, or network, with support for multi-turn conversations.", inputSchema: { type: "object", properties: { query: { type: "string", description: "The question or request about LinkedIn data to be analyzed." }, conversation_history: { type: "array", description: "Optional. Previous messages in the conversation for context. Each message must have 'role' (user/assistant) and 'content' (text).", items: { type: "object", properties: { role: { type: "string", description: "The sender of the message: 'user' or 'assistant'." }, content: { type: "string", description: "The text content of the message." } }, required: ["role", "content"] } } }, required: ["query"] } }, { name: "generate_linkedin_post", description: "Generate three LinkedIn post variants from any content (article, newsletter, notes, etc.) to optimize engagement.", inputSchema: { type: "object", properties: { content: { type: "string", description: "The source content to transform into LinkedIn posts. Can be articles, emails, newsletters, notes, etc." }, content_type: { type: "string", description: "Optional. A short description of the content type (e.g., 'article', 'newsletter', 'notes'). Defaults to 'article'." } }, required: ["content"] } }, { name: "get_linkedin_posts", description: "Retrieve the user's recent LinkedIn posts with engagement metrics.", inputSchema: { type: "object", properties: { limit: { type: "number", description: "Optional. Number of posts to retrieve (1-20). Defaults to 5." } } } }, { name: "get_linkedin_profile", description: "Retrieve the user's LinkedIn profile information including headline, summary, experience, and education.", inputSchema: { type: "object", properties: {} } }, { name: "set_linkedin_url", description: "Set or update the LinkedIn profile URL to analyze. Required before using profile/posts retrieval tools if not set previously.", inputSchema: { type: "object", properties: { linkedin_url: { type: "string", description: "The full LinkedIn profile URL (e.g., https://www.linkedin.com/in/username/)" } }, required: ["linkedin_url"] } }, { name: "refresh_linkedin_profile", description: "Force a refresh of the LinkedIn profile data to update any recent changes.", inputSchema: { type: "object", properties: {} } }, { name: "refresh_linkedin_posts", description: "Force a refresh of LinkedIn posts data to capture recently published content.", inputSchema: { type: "object", properties: {} } } ] } });
• cli.js:14-14 (helper)

  Backend API endpoint URL used by the analyze_linkedin_chat handler.
  const backendAnalyzeChatApiUrl = 'https://ligo.ertiqah.com/api/mcp/analyze-linkedin-chat';