# How to integrate Jobnimbus MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Jobnimbus MCP with Vercel AI SDK v6", "toolkit": "Jobnimbus", "toolkit_slug": "jobnimbus", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/jobnimbus/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/jobnimbus/framework/ai-sdk.md", "updated_at": "2026-05-12T10:16:29.914Z" } ``` ## Introduction This guide walks you through connecting Jobnimbus to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Jobnimbus agent that can list all open tasks for this week, create a new material order for a contact, fetch details for contact by name through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Jobnimbus account through Composio's Jobnimbus MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Jobnimbus with - [OpenAI Agents SDK](https://composio.dev/toolkits/jobnimbus/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/jobnimbus/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/jobnimbus/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/jobnimbus/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/jobnimbus/framework/codex) - [OpenClaw](https://composio.dev/toolkits/jobnimbus/framework/openclaw) - [Hermes](https://composio.dev/toolkits/jobnimbus/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/jobnimbus/framework/cli) - [Google ADK](https://composio.dev/toolkits/jobnimbus/framework/google-adk) - [LangChain](https://composio.dev/toolkits/jobnimbus/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/jobnimbus/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/jobnimbus/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/jobnimbus/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Jobnimbus integration - Using Composio's Tool Router to dynamically load and access Jobnimbus tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the Jobnimbus MCP server, and what's possible with it? The Jobnimbus MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Jobnimbus account. It provides structured and secure access to your CRM and project management data, so your agent can perform actions like managing contacts, scheduling tasks, creating locations, and retrieving account information on your behalf. - Contact management and lookup: Instantly create new contacts or fetch full details and lists of existing contacts for streamlined project tracking and reporting. - Task scheduling and tracking: Direct your agent to create and assign tasks, helping teams stay organized and on top of project to-dos. - Location and job site creation: Quickly add new locations to your Jobnimbus account, ensuring every job and address is properly logged for future reference. - Material order and workflow automation: Let your agent place material orders for jobs and update workflow statuses to keep projects moving smoothly from lead to completion. - Account and attachment management: Retrieve account settings or pull file attachments by ID, supporting seamless document handling and system configuration. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `JOBNIMBUS_ACCOUNT_CREATE_LOCATION` | Create Location | Tool to create a new location in JobNimbus. Use after gathering address and contact details. | | `JOBNIMBUS_ACCOUNT_GET_SETTINGS` | Get Account Settings | Tool to retrieve account-wide settings (workflows, types, sources). Use after authenticating to load or refresh workflow and source mappings. | | `JOBNIMBUS_ACTIVITY_GET` | Get Activity by ID | Retrieves a specific JobNimbus activity by its unique jnid. Activities in JobNimbus represent logged events such as task modifications, contact updates, job creation, and other system actions. Each activity contains details about what changed, who made the change, and when it occurred. Use this action when you need detailed information about a specific activity, such as viewing the full history of changes or understanding who performed an action. | | `JOBNIMBUS_CONTACT_GET` | Get Contact by ID | Tool to retrieve a contact by ID. Use after obtaining the contact’s jnid to fetch full details. | | `JOBNIMBUS_CONTACT_LIST` | List Contacts | Tool to list all contacts. Use when you need to fetch multiple contacts, e.g., for reporting or synchronization. | | `JOBNIMBUS_CONTACT_UPDATE` | Update Contact | Tool to update an existing contact. Use when you have a contact's JNID and need to modify its fields. Call after fetching or creating a contact. | | `JOBNIMBUS_CREATE_FILE_TYPE` | Create File Attachment Type | Creates a new file attachment type in JobNimbus. File types are custom categories used to organize and classify document attachments (e.g., contracts, warranties, photos, permits). You must create a file type before you can upload files with that category. | | `JOBNIMBUS_CREATE_MATERIAL_ORDER` | Create Material Order | Creates a new material order in JobNimbus. A material order tracks materials needed for a job and can be submitted to suppliers. Material orders must be linked to a contact or job record and include at least one line item referencing an existing product from your Products & Services catalog. Prerequisites: - At least one contact or job record must exist (use JOBNIMBUS_CONTACT_LIST to find contacts) - Products must exist in your catalog (use JOBNIMBUS_LIST_PRODUCTS to find product IDs) Note: Custom line items are not supported - all items must reference existing products by their jnid. | | `JOBNIMBUS_CREATE_TASK` | Create Task | Tool to create a new task. Use when scheduling or tracking tasks linked to contacts or jobs. | | `JOBNIMBUS_CREATE_WORKFLOW_STATUS` | Create Workflow Status | Tool to create a new status in an existing workflow. Use after confirming the workflow ID to add specialized status entries like 'Lead' or 'Inspection'. | | `JOBNIMBUS_FILE_GET` | Get File Attachment Content by ID | Retrieves the raw content of a specific file attachment from JobNimbus by its unique ID. This action downloads the actual file content (binary data for PDFs, images, etc.) but does NOT return file metadata like filename, content type, or size. If you need metadata, use the files list endpoint instead. Common use case: Download a file attachment after obtaining its jnid from a list files query or from a related record (contact, job, etc.). | | `JOBNIMBUS_LIST_ACTIVITIES` | List Activities | Tool to retrieve all activities. Use after authentication to fetch a paginated list of activities. | | `JOBNIMBUS_LIST_INVOICES` | List Invoices | Tool to list all invoices (v2). Use when you need to fetch multiple invoice records. | | `JOBNIMBUS_LIST_MATERIAL_ORDERS` | List Material Orders | Tool to list all material orders (v2). Use after authentication to fetch multiple material order records. | | `JOBNIMBUS_LIST_PAYMENTS` | List Payments | Tool to retrieve payments list with optional filters. Use after auth. | | `JOBNIMBUS_LIST_PRODUCTS` | List Products | Tool to list all products. Use after authentication to fetch full product catalog. | | `JOBNIMBUS_LIST_WORKORDERS` | List Work Orders | Tool to retrieve all work orders (v2). Use after authentication when you need a paginated list of work orders. | | `JOBNIMBUS_PRODUCT_GET` | Get Product by ID | Retrieves detailed information about a specific JobNimbus product using its jnid. Use this action when you need to get full details about a product, including pricing, cost, unit of measurement, and tax settings. Obtain the jnid first using the List Products action. | | `JOBNIMBUS_TASK_LIST` | List Tasks | Tool to list all tasks. Use when you need an overview of tasks for planning or review. | | `JOBNIMBUS_UPDATE_TASK` | Update Task | Update an existing JobNimbus task by its jnid. Allows updating task details like title, description, dates, priority, and task type. Use List Tasks action to find task jnids. Note: To update task type, both record_type and record_type_name must be provided together. | | `JOBNIMBUS_UTILITY_GET_UOMS` | Get Units of Measure | Tool to retrieve list of supported units of measure. Use after authenticating when you need to present or validate measurement units. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Jobnimbus MCP server is an implementation of the Model Context Protocol that connects your AI agent to Jobnimbus. It provides structured and secure access so your agent can perform Jobnimbus operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Jobnimbus tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Jobnimbus-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["jobnimbus"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Jobnimbus tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to jobnimbus, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Jobnimbus tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["jobnimbus"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to jobnimbus, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Jobnimbus agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Jobnimbus MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/jobnimbus/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/jobnimbus/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/jobnimbus/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/jobnimbus/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/jobnimbus/framework/codex) - [OpenClaw](https://composio.dev/toolkits/jobnimbus/framework/openclaw) - [Hermes](https://composio.dev/toolkits/jobnimbus/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/jobnimbus/framework/cli) - [Google ADK](https://composio.dev/toolkits/jobnimbus/framework/google-adk) - [LangChain](https://composio.dev/toolkits/jobnimbus/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/jobnimbus/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/jobnimbus/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/jobnimbus/framework/crew-ai) ## Related Toolkits - [Hubspot](https://composio.dev/toolkits/hubspot) - HubSpot is an all-in-one marketing, sales, and customer service platform. It lets teams nurture leads, automate outreach, and track every customer interaction in one place. - [Pipedrive](https://composio.dev/toolkits/pipedrive) - Pipedrive is a sales management platform offering pipeline visualization, lead tracking, and workflow automation. It helps sales teams keep deals moving forward efficiently and never miss a follow-up. - [Salesforce](https://composio.dev/toolkits/salesforce) - Salesforce is a leading CRM platform that helps businesses manage sales, service, and marketing. It centralizes customer data, enabling teams to drive growth and build strong relationships. - [Apollo](https://composio.dev/toolkits/apollo) - Apollo is a CRM and lead generation platform that helps businesses discover contacts and manage sales pipelines. Use it to streamline customer outreach and track your deals from one place. - [Attio](https://composio.dev/toolkits/attio) - Attio is a customizable CRM and workspace for managing your team's relationships and workflows. It helps teams organize contacts, automate tasks, and collaborate more efficiently. - [Acculynx](https://composio.dev/toolkits/acculynx) - AccuLynx is a cloud-based roofing business management software for contractors. It streamlines project tracking, lead management, and document sharing. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Affinity](https://composio.dev/toolkits/affinity) - Affinity is a relationship intelligence CRM that helps private capital investors find, manage, and close more deals. It streamlines deal flow and surfaces key connections to help you win opportunities. - [Agencyzoom](https://composio.dev/toolkits/agencyzoom) - AgencyZoom is a sales and performance platform built for P&C insurance agencies. It helps agents boost sales, retain clients, and analyze producer results in one place. - [Bettercontact](https://composio.dev/toolkits/bettercontact) - Bettercontact is a smart contact enrichment tool for finding emails and phone numbers. It helps boost lead generation with automated, waterfall search across multiple sources. - [Blackbaud](https://composio.dev/toolkits/blackbaud) - Blackbaud provides cloud-based software for nonprofits, schools, and healthcare institutions. It streamlines fundraising, donor management, and mission-driven operations. - [Brilliant directories](https://composio.dev/toolkits/brilliant_directories) - Brilliant Directories is an all-in-one platform for building and managing online membership communities and business directories. It streamlines listings, member management, and engagement tools into a single, easy interface. - [Capsule crm](https://composio.dev/toolkits/capsule_crm) - Capsule CRM is a user-friendly CRM platform for managing contacts and sales pipelines. It helps businesses organize relationships and streamline their sales process efficiently. - [Centralstationcrm](https://composio.dev/toolkits/centralstationcrm) - CentralStationCRM is an easy-to-use CRM software focused on collaboration and long-term customer relationships. It helps teams manage contacts, deals, and communications all in one place. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time. - [Close](https://composio.dev/toolkits/close) - Close is a CRM platform built for sales teams, combining calling, email automation, and predictive dialers. It streamlines sales workflows and boosts productivity with all-in-one communication tools. - [Dropcontact](https://composio.dev/toolkits/dropcontact) - Dropcontact is a B2B email finder and data enrichment service for professionals. It delivers verified email addresses and enriches contact info with up-to-date data. - [Dynamics365](https://composio.dev/toolkits/dynamics365) - Dynamics 365 is Microsoft's platform combining CRM, ERP, and productivity apps. It streamlines sales, marketing, service, and operations in one place. - [Espocrm](https://composio.dev/toolkits/espocrm) - EspoCRM is an open-source web application for managing customer relationships. It helps businesses organize contacts, track leads, and streamline their sales process. - [Fireberry](https://composio.dev/toolkits/fireberry) - Fireberry is a CRM platform that streamlines customer and sales management. It helps businesses organize contacts, automate sales, and integrate with other business tools. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Jobnimbus MCP? With a standalone Jobnimbus MCP server, the agents and LLMs can only access a fixed set of Jobnimbus tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Jobnimbus and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Jobnimbus tools. ### Can I manage the permissions and scopes for Jobnimbus while using Tool Router? Yes, absolutely. You can configure which Jobnimbus scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Jobnimbus data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)