# How to integrate Geoapify MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Geoapify MCP with Vercel AI SDK v6", "toolkit": "Geoapify", "toolkit_slug": "geoapify", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/geoapify/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/geoapify/framework/ai-sdk.md", "updated_at": "2026-05-12T10:12:46.064Z" } ``` ## Introduction This guide walks you through connecting Geoapify to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Geoapify agent that can find latitude and longitude for an address, suggest address completions as i type, show reachable area within 10 minutes driving through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Geoapify account through Composio's Geoapify MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Geoapify with - [OpenAI Agents SDK](https://composio.dev/toolkits/geoapify/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/geoapify/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/geoapify/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/geoapify/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/geoapify/framework/codex) - [OpenClaw](https://composio.dev/toolkits/geoapify/framework/openclaw) - [Hermes](https://composio.dev/toolkits/geoapify/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/geoapify/framework/cli) - [Google ADK](https://composio.dev/toolkits/geoapify/framework/google-adk) - [LangChain](https://composio.dev/toolkits/geoapify/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/geoapify/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/geoapify/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/geoapify/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Geoapify integration - Using Composio's Tool Router to dynamically load and access Geoapify 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 Geoapify MCP server, and what's possible with it? The Geoapify MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Geoapify account. It provides structured and secure access to powerful location-based services, so your agent can perform actions like geocoding addresses, generating routes, fetching map tiles, and analyzing geographic data on your behalf. - Address autocomplete and geocoding: Instantly convert partial or full addresses into geographic coordinates, or fetch smart suggestions to speed up location entry. - Routing and reachability analysis: Generate routes, calculate reachable areas (isochrones/isodistances), and let your agent determine how far you can travel from a point within a set time or distance. - IP-based geolocation: Look up the approximate location of any IP address to enrich user data, personalize experiences, or detect regions automatically. - Map visualization and customization: Fetch custom-styled map tiles and create personalized marker icons for fully tailored map displays in your applications or reports. - Boundary and geometry operations: Retrieve administrative boundaries for any place or coordinate, and perform advanced geometric operations like combining or intersecting polygons to analyze spatial relationships. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `GEOAPIFY_ADDRESS_AUTOCOMPLETE` | Address Autocomplete | Tool to fetch address suggestions based on partial input. Use when you need to get predictive suggestions from incomplete address text. | | `GEOAPIFY_BATCH_REQUESTS` | Batch Requests | Create or retrieve asynchronous batch processing jobs for geocoding, reverse geocoding, routing, or isoline APIs. Use cases: - Batch geocode up to 1000 addresses at once (forward geocoding) - Batch reverse geocode multiple coordinates - Process multiple routing or isoline requests in one batch Workflow: 1. Create a job by providing 'api' and 'inputs' (returns job ID and status 'pending') 2. Poll the job by providing 'id' until status changes from 'pending' to complete (results available) | | `GEOAPIFY_BOUNDARIES` | Get Boundaries Containing Location | Retrieve all administrative boundaries that contain a given location. Returns hierarchical boundaries (suburb, city, county, state, country) as GeoJSON features. Use this to find what administrative areas a coordinate belongs to, get boundary polygons for mapping, or identify postal codes and political districts for a location. | | `GEOAPIFY_CREATE_BATCH_FORWARD_GEOCODE_JOB` | Create Batch Forward Geocode Job | Tool to create a batch forward geocoding job for up to 1000 addresses. Use when you need to geocode multiple addresses asynchronously. Returns a job ID for retrieving results once processing is complete. | | `GEOAPIFY_CREATE_BATCH_REVERSE_GEOCODE_JOB` | Create Batch Reverse Geocode Job | Tool to create a batch reverse geocoding job that converts multiple lat/lon coordinates into addresses asynchronously. Use when you need to reverse geocode multiple coordinates (up to 1000) in one request. Returns a job ID for retrieving results. | | `GEOAPIFY_FORWARD_GEOCODING` | Forward Geocoding | Tool to convert an address into geographic coordinates. Use when you need latitude and longitude from an address. | | `GEOAPIFY_GEOMETRY` | Geometry Operation | Tool to perform geometric operations on stored polygon geometries. Use when combining or intersecting multiple stored geometries. | | `GEOAPIFY_GET_BATCH_FORWARD_GEOCODE_RESULTS` | Get Batch Forward Geocode Results | Tool to retrieve batch forward geocoding job results using the job ID. Use when you need to fetch geocoded addresses from a previously submitted batch job. Results available in JSON or CSV format. Job must be complete (status 200) to get results. | | `GEOAPIFY_GET_BATCH_REVERSE_GEOCODE_RESULTS` | Get Batch Reverse Geocode Results | Tool to retrieve batch reverse geocoding job results. Use when you have a batch job ID from creating a batch reverse geocoding job and want to fetch the completed results. | | `GEOAPIFY_GET_BOUNDARIES_CONSISTS_OF` | Get Child Boundaries (Consists Of) | Get boundaries that a specified location consists of. Returns child administrative divisions (states for country, districts for city). Useful for drilling down into sub-regions. | | `GEOAPIFY_GET_MAP_STYLE` | Get Map Style JSON | Tool to retrieve vector map style JSON for MapLibre GL and Mapbox GL. Returns a Mapbox-compatible style specification for rendering vector tiles. | | `GEOAPIFY_GET_STATIC_MAP` | Generate Static Map Image | Tool to generate static map images with customizable style, size, center, zoom, markers, and geometries. Use when you need a map image for display or printing. | | `GEOAPIFY_IP_GEOLOCATION` | IP Geolocation | Lookup geographic location information for an IP address. Returns city-level location data including country, region, city, coordinates, and additional metadata like currency and language. If no IP is provided, returns location for the caller's IP address. | | `GEOAPIFY_ISOLINE` | Generate isoline (isochrone/isodistance) | Tool to generate isochrone or isodistance isolines. Use when visualizing reachable areas from a point; use `id` to poll ongoing calculations. | | `GEOAPIFY_LIST_POSTCODES` | List Postcodes | Tool to list postcodes within a specified area or boundary. Use when you need to retrieve multiple postcodes in a geographic region using filters like circle, rectangle, or place ID. | | `GEOAPIFY_MAP_MATCHING` | Map Matching | Snap GPS traces to the road network for accurate route reconstruction. Use this tool to: - Correct GPS drift and inaccuracies in recorded tracks - Align vehicle/cycling/walking traces to actual roads - Get road names and properties along the matched route - Calculate accurate distance and travel time from GPS data | | `GEOAPIFY_MAP_TILES` | Fetch Geoapify Map Tiles | Tool to fetch raster map tiles or style JSON from Geoapify. Use when rendering custom maps with specific styles. | | `GEOAPIFY_MARKER_ICON` | Create Marker Icon | Generate custom map marker icons as PNG images. Creates customizable marker icons for use in mapping applications (Leaflet, MapLibre GL, Google Maps, etc.). Supports multiple styles (material, circle, plain), custom colors, icons from Material Design and Font Awesome libraries, or custom text/numbers. Example use cases: - Create a red location pin with a star icon - Generate numbered markers (1, 2, 3...) for route waypoints - Create custom-colored markers matching your brand | | `GEOAPIFY_PLACE_DETAILS` | Place Details | Tool to retrieve detailed information about a specific place. Use when you have a place ID or coordinates and need comprehensive metadata. | | `GEOAPIFY_PLACES` | Places Search | Search for points of interest (POIs) like restaurants, hotels, attractions, hospitals, etc. within a geographic area. Use this tool when you need to find places by category near a location. You must provide either a 'filter' (to search within a bounded area) or 'bias' (to rank results by proximity to a point). Common use cases: - Find restaurants near a location: categories=['catering.restaurant'], bias='proximity:lon,lat' - Search for hotels in a city area: categories=['accommodation.hotel'], filter='circle:lon,lat,5000' - Find wheelchair-accessible attractions: categories=['tourism.attraction'], conditions=['wheelchair'] | | `GEOAPIFY_POSTCODE` | Postcode Search | Tool to retrieve postcode information for a location. Use when you need to fetch postcode details based on a given postcode or geographic coordinates. | | `GEOAPIFY_REVERSE_GEOCODING` | Reverse Geocoding | Tool to reverse geocode coordinates into a structured address. Use when converting lat/lon to human-readable addresses. | | `GEOAPIFY_ROUTE_MATRIX` | Route Matrix | Tool to compute travel time and distance matrices. Use when you need durations and distances between multiple origin and destination pairs. | | `GEOAPIFY_ROUTE_PLANNER` | Route Planner | Optimize multi-agent routes for deliveries, pickups, and service jobs. Solves Vehicle Routing Problems (VRP) including: Travelling Salesman (TSP), Capacitated VRP, VRP with Time Windows, and Pickup-Delivery problems. Required: Either 'jobs' (one-way tasks) or 'shipments' (pickup-delivery pairs). Coordinates: Use [longitude, latitude] format (not lat/lon). | | `GEOAPIFY_ROUTING` | Routing | Tool to calculate routes between multiple waypoints. Use when you need both distance, time, and turn-by-turn directions for two or more coordinates. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Geoapify MCP server is an implementation of the Model Context Protocol that connects your AI agent to Geoapify. It provides structured and secure access so your agent can perform Geoapify 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 Geoapify 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 Geoapify-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: ["geoapify"], }); 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 Geoapify 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 geoapify, 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 Geoapify 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: ["geoapify"], }); 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 geoapify, 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 Geoapify 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 Geoapify MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/geoapify/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/geoapify/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/geoapify/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/geoapify/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/geoapify/framework/codex) - [OpenClaw](https://composio.dev/toolkits/geoapify/framework/openclaw) - [Hermes](https://composio.dev/toolkits/geoapify/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/geoapify/framework/cli) - [Google ADK](https://composio.dev/toolkits/geoapify/framework/google-adk) - [LangChain](https://composio.dev/toolkits/geoapify/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/geoapify/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/geoapify/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/geoapify/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. 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It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements. - [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints. - [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots. - [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches. - [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. 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It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Geoapify MCP? With a standalone Geoapify MCP server, the agents and LLMs can only access a fixed set of Geoapify tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Geoapify 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 Geoapify tools. ### Can I manage the permissions and scopes for Geoapify while using Tool Router? Yes, absolutely. You can configure which Geoapify 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 Geoapify data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)