# How to integrate Bitquery MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Bitquery MCP with Vercel AI SDK v6", "toolkit": "Bitquery", "toolkit_slug": "bitquery", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/bitquery/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/bitquery/framework/ai-sdk.md", "updated_at": "2026-05-12T10:03:11.370Z" } ``` ## Introduction This guide walks you through connecting Bitquery to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Bitquery agent that can show real-time ethereum mempool transactions, count unique wallet addresses for solana, query historical bitcoin transactions from 2021 through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Bitquery account through Composio's Bitquery MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Bitquery with - [OpenAI Agents SDK](https://composio.dev/toolkits/bitquery/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/bitquery/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/bitquery/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/bitquery/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/bitquery/framework/codex) - [OpenClaw](https://composio.dev/toolkits/bitquery/framework/openclaw) - [Hermes](https://composio.dev/toolkits/bitquery/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/bitquery/framework/cli) - [Google ADK](https://composio.dev/toolkits/bitquery/framework/google-adk) - [LangChain](https://composio.dev/toolkits/bitquery/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/bitquery/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/bitquery/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/bitquery/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Bitquery integration - Using Composio's Tool Router to dynamically load and access Bitquery 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 Bitquery MCP server, and what's possible with it? The Bitquery MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bitquery account. It provides structured and secure access to blockchain datasets and real-time analytics, so your agent can perform actions like querying historical transactions, streaming mempool activity, selecting blockchain networks, and aggregating metrics across 40+ supported chains. - Seamless blockchain data querying: Let your agent run powerful queries on historical or real-time blockchain data across multiple networks using Bitquery's combined or archive databases. - Live mempool monitoring: Subscribe and stream pending transactions from EVM-compatible chains in real time, enabling instant insights into network activity as it happens. - On-demand network and database selection: Have your agent dynamically select blockchain networks and datasets—like Ethereum, BNB Chain, or others—to tailor queries for your specific use case. - Metric aggregation and analysis: Automate the aggregation of transaction counts, unique values, or conditional metrics, empowering your agent to analyze blockchain trends without manual intervention. - Advanced GraphQL customization: Use aliases and conditional snippets to refine data responses, ensuring clarity and precise control in complex blockchain analytics workflows. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BITQUERY_ARCHIVE_DATABASE_QUERY` | Archive Database Query | Query the Bitquery Archive Database (V1 API) for historical blockchain data. The Archive Database provides complete historical blockchain data across 40+ blockchains including Bitcoin, Ethereum, BSC, Solana, and more. Data has a delay of tens of minutes to hours from real-time. For near-real-time data, use the Realtime Database Query instead. The V1 API uses blockchain-specific root types (bitcoin, ethereum, etc.) with fields like blocks, transactions, transfers, and trades. Queries support filtering, pagination with limit/offset, and sorting with orderBy. Example queries: - Bitcoin blocks: { bitcoin { blocks(limit: 5, orderBy: {descending: height}) { height } } } - Ethereum transactions: { ethereum { transactions(limit: 10) { hash value } } } | | `BITQUERY_COMBINED_DATABASE_QUERY` | Combined Database Query | Query Bitquery's Combined Database (v2 API) for blockchain data across 40+ networks. Use this tool to fetch real-time and historical blockchain data including: - Blocks, transactions, and events - Token transfers and balances - DEX trades and liquidity data - Smart contract interactions - NFT data and metadata Supported networks include: Ethereum (eth), BSC (bsc), Polygon (matic), Solana, Tron, and more. The v2 API uses a different schema than v1 - use EVM(network: eth) instead of ethereum root field. | | `BITQUERY_CONDITIONAL_METRICS` | Conditional Metrics Snippet | Generate a Bitquery GraphQL metric snippet with conditional logic using the 'if:' attribute. This tool builds metric aggregation snippets (count, sum, avg, min, max) that can be embedded in Bitquery GraphQL queries. The 'if:' filter allows applying conditions directly to metric calculations, enabling conditional aggregation like counting only successful transactions. Output format examples: - count(if: {Block: {GasUsed: {gt: "0"}}}) - sum(of: Block_GasUsed if: {Block: {Time: {after: "2024-01-01"}}}) - myAlias: avg(of: Transaction_Value if: {Transaction: {Success: true}}) | | `BITQUERY_DATABASE_SELECTION` | Database Selection | Tool to select the database (archive, realtime, combined) to query at the top level of a GraphQL request. Use after determining whether you need live, historical, or combined blockchain data. | | `BITQUERY_EARLY_ACCESS_PROGRAM_QUERY` | Early Access Program Query | Execute GraphQL queries against the Bitquery Early Access Program (EAP) Streaming API. This tool queries the EAP endpoint (streaming.bitquery.io/eap) for real-time blockchain data. The EAP provides access to streaming data across various blockchain networks including Solana, EVM chains (Ethereum, Polygon, etc.), and others for evaluation purposes. Key features: - Real-time blockchain data with minimal latency - Supports both queries and subscriptions - Networks: Solana, Ethereum, Polygon (Matic), and other EVM-compatible chains Note: EAP is limited to real-time data only. For historical data, use the Archive Database Query. Existing users can continue using EAP; new users should prefer the V2 endpoint for most use cases. Example queries: - Get latest ETH blocks: { EVM(network: eth) { Blocks(limit: {count: 5}) { Block { Number Time } } } } - Solana DEX trades: subscription { Solana { DEXTrades { Block { Time } Trade { Price } } } } | | `BITQUERY_NETWORK_SELECTION` | Network Selection | Tool to select the blockchain network for GraphQL queries. Use before constructing dataset or metric queries to ensure the correct chain is targeted. | | `BITQUERY_OPTIONS_QUERY` | Options Query | Tool to fetch GraphQL dataset options via schema introspection. Use when you need to discover root-level query fields and their arguments before building queries. Dataset and token availability varies by Bitquery environment; verify available fields here before constructing complex queries that depend on specific datasets. | | `BITQUERY_PRICE_ASYMMETRY_METRIC` | Price Asymmetry Metric | Tool to generate GraphQL PriceAsymmetry filter snippet. Use when you need to filter trades based on price asymmetry metric. | | `BITQUERY_REALTIME_DATABASE_QUERY` | Realtime Database Query | Query the Bitquery Streaming (V2) API for realtime blockchain data. This tool accesses the Bitquery Streaming API at streaming.bitquery.io/graphql which provides real-time blockchain data with minimal latency. Use this for recent data (within minutes). For historical data, use the Archive Database Query. Supported query formats: - V2 EVM queries: { EVM(network: eth) { Blocks(limit: {count: 5}) { Block { Number Time } } } } - V2 Bitcoin queries: { bitcoin(network: bitcoin) { blocks(limit: {count: 5}) { height timestamp { time } } } } Note: Requires an active Bitquery subscription for streaming API access. | | `BITQUERY_SELECT_BY_METRIC` | Select By Metric | Tool to generate a GraphQL metric snippet filtering by its value using selectWhere. Use when you need to include only metrics meeting specific value conditions (e.g., only positive sums). | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Bitquery MCP server is an implementation of the Model Context Protocol that connects your AI agent to Bitquery. It provides structured and secure access so your agent can perform Bitquery 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 Bitquery 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 Bitquery-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: ["bitquery"], }); 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 Bitquery 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 bitquery, 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 Bitquery 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: ["bitquery"], }); 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 bitquery, 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 Bitquery 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 Bitquery MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/bitquery/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/bitquery/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/bitquery/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/bitquery/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/bitquery/framework/codex) - [OpenClaw](https://composio.dev/toolkits/bitquery/framework/openclaw) - [Hermes](https://composio.dev/toolkits/bitquery/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/bitquery/framework/cli) - [Google ADK](https://composio.dev/toolkits/bitquery/framework/google-adk) - [LangChain](https://composio.dev/toolkits/bitquery/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/bitquery/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/bitquery/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/bitquery/framework/crew-ai) ## Related Toolkits - [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management. - [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters. - [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort. - [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. - [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations. - [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions. - [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows. - [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations. - [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. 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. Developers use it to access fresh, low-latency SERP data on demand. - [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance. - [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows. - [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses. - [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction. - [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation. - [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation. - [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Bitquery MCP? With a standalone Bitquery MCP server, the agents and LLMs can only access a fixed set of Bitquery tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Bitquery 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 Bitquery tools. ### Can I manage the permissions and scopes for Bitquery while using Tool Router? Yes, absolutely. You can configure which Bitquery 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 Bitquery data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)