oraichainMCPClient.ts•6.13 kB
import * as readline from "readline";
import { AIMessage, BaseMessage, HumanMessage } from "@langchain/core/messages";
import {
CompiledStateGraph,
MemorySaver,
StateType,
} from "@langchain/langgraph";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { ChatMistralAI } from "@langchain/mistralai";
import "dotenv/config";
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import { Runnable, RunnableToolLike } from "@langchain/core/runnables";
import { BindToolsInput } from "@langchain/core/language_models/chat_models";
import { DynamicJsonSchema, jsonSchemaToZod } from "./utils";
// Configuration
// MCP Message interface
interface MCPMessage {
type: string;
context?: string;
data?: any;
}
function validateEnvironment(): void {
const missingVars: string[] = [];
const requiredVars = ["MISTRAL_API_KEY"];
requiredVars.forEach((varName) => {
if (!process.env[varName]) {
missingVars.push(varName);
}
});
if (missingVars.length > 0) {
console.error("Error: Required environment variables are not set");
missingVars.forEach((varName) => {
console.error(`${varName}=your_${varName.toLowerCase()}_here`);
});
process.exit(1);
}
}
validateEnvironment();
async function initializeAgent(tools: BindToolsInput[]) {
const llm = new ChatMistralAI({
modelName: "mistral-large-latest",
temperature: 0.3,
apiKey: process.env.MISTRAL_API_KEY!,
});
const memory = new MemorySaver();
return createReactAgent({
llm,
tools: tools as RunnableToolLike[],
// checkpointSaver: memory,
messageModifier: `
You are a helpful agent running on the client side. You can process prompts locally and call the MCP server
for blockchain interactions using the 'mcp_tool'. Be concise and helpful. If a tool call fails with a 5XX error,
ask the user to try again later. If the user requests something beyond your tools, suggest they implement it
using the Oraichain Agent Kit.
`,
});
}
class MCPClient {
constructor(
private readonly mcp: Client,
private readonly agent: CompiledStateGraph<StateType<{}>, any>,
) {}
static async connectToServer(serverScriptPath: string) {
// Initialize transport and connect to server
// Determine script type and appropriate command
const isJs = serverScriptPath.endsWith(".js");
const isTs = serverScriptPath.endsWith(".ts");
const isPy = serverScriptPath.endsWith(".py");
if (!isJs && !isPy && !isTs) {
throw new Error("Server script must be a .js, .ts or .py file");
}
const command = isPy
? process.platform === "win32"
? "python"
: "python3"
: "tsx";
const transport = new StdioClientTransport({
command,
args: [serverScriptPath],
});
const mcp = new Client({ name: "mcp-client-cli", version: "1.0.0" });
mcp.connect(transport);
const toolsResult = await mcp.listTools();
const tools = toolsResult.tools.map((tool) => ({
name: tool.name,
description: tool.description!,
schema: jsonSchemaToZod(tool.inputSchema as DynamicJsonSchema),
}));
const agent = await initializeAgent(tools);
const client = new MCPClient(mcp, agent);
// List available tools
return client;
}
async processQuery(query: string) {
/**
* Process a query using Claude and available tools
*
* @param query - The user's input query
* @returns Processed response as a string
*/
const response = await this.agent.invoke({
messages: [new HumanMessage(query)],
});
// console.debug("response: ", response.messages);
// Process response and handle tool calls
const finalText: any[] = [];
for (const msg of response.messages) {
if (msg instanceof AIMessage) {
if (msg.tool_calls && msg.tool_calls.length > 0) {
// Handle tool calls
for (const toolCall of msg.tool_calls) {
// console.debug("tool call: ", toolCall);
const result = await this.mcp.callTool({
name: toolCall.name,
arguments: toolCall.args,
});
const response = await this.agent.invoke({
messages: [new HumanMessage(JSON.stringify(result.content))],
});
// console.debug("response: ", response);
finalText.push(
response.messages[response.messages.length - 1].content,
);
}
}
}
}
return finalText.join("\n");
}
async chatLoop() {
/**
* Run an interactive chat loop
*/
const rl = readline.createInterface({
input: process.stdin,
output: process.stdout,
});
try {
console.log("\nMCP Client Started!");
console.log("Type your queries or 'quit' to exit.");
while (true) {
const message: string = await new Promise((resolve) =>
rl.question("\nQuery: ", (answer) => resolve(answer)),
);
if (message.toLowerCase() === "quit") {
break;
}
try {
const response = await this.processQuery(message);
console.log("\n" + response);
} catch (error) {
console.error("Error processing query:", error);
}
}
} finally {
rl.close();
}
}
async cleanup() {
/**
* Clean up resources
*/
await this.mcp.close();
}
}
async function main() {
if (process.argv.length < 3) {
console.log("Usage: node build/index.js <path_to_server_script>");
return;
}
const mpcClient = await MCPClient.connectToServer(process.argv[2]);
try {
await mpcClient.chatLoop();
} finally {
await mpcClient.cleanup();
process.exit(0);
}
}
main();
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