MCP AI Agent
A TypeScript library that enables AI agents to leverage MCP (Model Context Protocol) servers for enhanced capabilities. This library integrates with the AI SDK to provide a seamless way to connect to MCP servers and use their tools in AI-powered appl
What is MCP AI Agent?
MCP AI Agent is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to typescript library that enables ai agents to leverage mcp (model context protocol) servers for enhanced capabilities. this library integrates with the ai sdk to provide a seamless way to connect to mc...
A TypeScript library that enables AI agents to leverage MCP (Model Context Protocol) servers for enhanced capabilities. This library integrates with the AI SDK to provide a seamless way to connect to MCP servers and use their tools in AI-powered appl
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A TypeScript library that enables AI agents to leverage MCP
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx mcp-ai-agentConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use MCP AI Agent
MCP AI Agent is a TypeScript library that lets you build AI agents that transparently connect to any MCP server and use its tools as native capabilities — integrating with AI SDK v5 for text generation and tool calling. It supports multiple transport methods (STDIO and SSE), multi-agent composition where specialized agents can call each other, custom tool definitions alongside MCP tools, and a CrewAI-style workflow pattern. Developers building agentic applications use it to wire together MCP servers and LLMs without managing the underlying protocol plumbing.
Prerequisites
- Node.js 18 or higher
- An npm project with TypeScript support
- API keys for the LLM provider you want to use (e.g. OPENAI_API_KEY for OpenAI models via @ai-sdk/openai, or equivalent for Anthropic/other providers)
- At least one MCP server to connect to (e.g. @modelcontextprotocol/server-memory, or any other MCP server)
Install the library
Install mcp-ai-agent and an AI SDK provider package in your Node.js project.
npm install mcp-ai-agent
npm install @ai-sdk/openai # or @ai-sdk/anthropic, etc.Create a basic agent with a preconfigured MCP server
Import AIAgent and use one of the preconfigured Servers or define your own MCP server config. The agent auto-initializes — no explicit initialize() call needed.
import { AIAgent, Servers } from "mcp-ai-agent";
import { openai } from "@ai-sdk/openai";
const agent = new AIAgent({
name: "My Agent",
description: "An agent with sequential thinking",
model: openai("gpt-4o-mini"),
toolsConfigs: [Servers.sequentialThinking],
});
const response = await agent.generateResponse({
prompt: "Break down the steps to build a REST API",
});
console.log(response.text);Define a custom MCP server connection
You can connect to any MCP server by providing its command and args directly in toolsConfigs, just like a standard MCP client configuration.
import { AIAgent } from "mcp-ai-agent";
import { openai } from "@ai-sdk/openai";
const agent = new AIAgent({
name: "Memory Agent",
description: "Stores and retrieves memories",
model: openai("gpt-4o-mini"),
toolsConfigs: [
{
mcpServers: {
memory: {
command: "npx",
args: ["-y", "@modelcontextprotocol/server-memory"],
},
},
},
],
});Compose multi-agent workflows
Create specialized agents and compose them under a master agent that can delegate tasks. Each sub-agent becomes a callable tool for the master agent.
import { AIAgent, Servers } from "mcp-ai-agent";
import { openai } from "@ai-sdk/openai";
const searchAgent = new AIAgent({
name: "Search Agent",
description: "Searches the web for information",
model: openai("gpt-4o-mini"),
toolsConfigs: [Servers.braveSearch],
});
const masterAgent = new AIAgent({
name: "Master Agent",
description: "Orchestrates specialized agents",
model: openai("gpt-4o"),
toolsConfigs: [{ type: "agent", agent: searchAgent }],
});Set your LLM provider API key and run
Export your API key as an environment variable and run your agent script.
export OPENAI_API_KEY=sk-...
node --loader ts-node/esm your_agent.tsMCP AI Agent Examples
Client configuration
This is a library, not a standalone server. The equivalent config shows how to reference a custom MCP server within the library's toolsConfigs.
{
"toolsConfigs": [
{
"mcpServers": {
"memory": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-memory"]
}
}
}
]
}Prompts to try
Example prompts you can pass to agent.generateResponse() in your application code.
- "What is the latest Bitcoin price? Store the answer in memory."
- "What information have we stored about Bitcoin price?"
- "Break down the Website project requirements into tasks and estimate time for each"
- "Search the web for the current status of the Node.js v22 LTS release"
- "Use sequential thinking to solve: I have 3 apples, give away 2, buy 5 more. How many do I have?"Troubleshooting MCP AI Agent
Agent throws 'Cannot find module mcp-ai-agent' or TypeScript import errors
Run 'npm install mcp-ai-agent' to ensure the package is installed. For TypeScript, ensure your tsconfig.json has 'moduleResolution' set to 'bundler' or 'node16' and 'module' set to 'ESNext' or 'NodeNext'. Check the mcp-ai-agent-example repo for a working tsconfig reference.
MCP server subprocess fails to start inside the agent
The command specified in mcpServers (e.g. 'npx') must be available in the PATH of the Node.js process running your agent. Test the command manually in your terminal first. For STDIO transport, the MCP server must read from stdin and write to stdout in JSON-RPC format.
Multi-agent workflow: sub-agent is never called by the master agent
Ensure the sub-agent has a clear 'description' field — the master agent's LLM uses this to decide when to delegate. Also confirm the master agent's model is powerful enough for tool orchestration (gpt-4o or equivalent is recommended over gpt-4o-mini for routing decisions).
Frequently Asked Questions about MCP AI Agent
What is MCP AI Agent?
MCP AI Agent is a Model Context Protocol (MCP) server that typescript library that enables ai agents to leverage mcp (model context protocol) servers for enhanced capabilities. this library integrates with the ai sdk to provide a seamless way to connect to mcp servers and use their tools in ai-powered appl It connects AI assistants to external tools and data sources through a standardized interface.
How do I install MCP AI Agent?
Follow the installation instructions on the MCP AI Agent GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with MCP AI Agent?
MCP AI Agent works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is MCP AI Agent free to use?
Yes, MCP AI Agent is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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