index.js•6.65 kB
#!/usr/bin/env node
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
CallToolRequestSchema,
ListToolsRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";
import { GoogleGenerativeAI } from "@google/generative-ai";
// Initialize Gemini API
const GEMINI_API_KEY = process.env.GEMINI_API_KEY;
if (!GEMINI_API_KEY) {
console.error("Error: GEMINI_API_KEY environment variable is required");
process.exit(1);
}
const genAI = new GoogleGenerativeAI(GEMINI_API_KEY);
// Create MCP server
const server = new Server(
{
name: "gemini-mcp-server",
version: "1.0.0",
},
{
capabilities: {
tools: {},
},
}
);
// Define available tools
server.setRequestHandler(ListToolsRequestSchema, async () => {
return {
tools: [
{
name: "gemini_chat",
description: "Send a message to Google Gemini 2.5 Pro and get a response",
inputSchema: {
type: "object",
properties: {
message: {
type: "string",
description: "The message to send to Gemini",
},
temperature: {
type: "number",
description: "Controls randomness (0.0-2.0). Default: 1.0",
default: 1.0,
},
max_tokens: {
type: "number",
description: "Maximum tokens in response. Default: 8192",
default: 8192,
},
},
required: ["message"],
},
},
{
name: "gemini_chat_with_history",
description: "Multi-turn conversation with Gemini maintaining context",
inputSchema: {
type: "object",
properties: {
messages: {
type: "array",
description: "Array of conversation messages [{role: 'user'|'model', parts: [{text: 'message'}]}]",
items: {
type: "object",
properties: {
role: { type: "string", enum: ["user", "model"] },
parts: {
type: "array",
items: {
type: "object",
properties: {
text: { type: "string" }
}
}
}
}
}
},
temperature: {
type: "number",
description: "Controls randomness (0.0-2.0). Default: 1.0",
default: 1.0,
},
},
required: ["messages"],
},
},
{
name: "gemini_analyze_code",
description: "Analyze code using Gemini for bugs, improvements, or explanations",
inputSchema: {
type: "object",
properties: {
code: {
type: "string",
description: "The code to analyze",
},
language: {
type: "string",
description: "Programming language (e.g., javascript, python, go)",
},
analysis_type: {
type: "string",
description: "Type of analysis: 'bugs', 'optimize', 'explain', 'review'",
enum: ["bugs", "optimize", "explain", "review"],
default: "review",
},
},
required: ["code"],
},
},
],
};
});
// Handle tool execution
server.setRequestHandler(CallToolRequestSchema, async (request) => {
const { name, arguments: args } = request.params;
try {
switch (name) {
case "gemini_chat": {
const model = genAI.getGenerativeModel({
model: "gemini-2.0-flash-exp",
generationConfig: {
temperature: args.temperature || 1.0,
maxOutputTokens: args.max_tokens || 8192,
},
});
const result = await model.generateContent(args.message);
const response = result.response;
const text = response.text();
return {
content: [
{
type: "text",
text: text,
},
],
};
}
case "gemini_chat_with_history": {
const model = genAI.getGenerativeModel({
model: "gemini-2.0-flash-exp",
generationConfig: {
temperature: args.temperature || 1.0,
maxOutputTokens: 8192,
},
});
const chat = model.startChat({
history: args.messages.slice(0, -1),
});
const lastMessage = args.messages[args.messages.length - 1];
const result = await chat.sendMessage(lastMessage.parts[0].text);
const text = result.response.text();
return {
content: [
{
type: "text",
text: text,
},
],
};
}
case "gemini_analyze_code": {
const analysisPrompts = {
bugs: `Analyze the following ${args.language || ''} code for bugs, errors, and potential issues:\n\n${args.code}\n\nProvide a detailed bug report.`,
optimize: `Review the following ${args.language || ''} code and suggest performance optimizations and best practices:\n\n${args.code}`,
explain: `Explain the following ${args.language || ''} code in detail, including what it does and how it works:\n\n${args.code}`,
review: `Perform a comprehensive code review of the following ${args.language || ''} code, covering bugs, performance, security, and best practices:\n\n${args.code}`,
};
const prompt = analysisPrompts[args.analysis_type || 'review'];
const model = genAI.getGenerativeModel({
model: "gemini-2.0-flash-exp",
});
const result = await model.generateContent(prompt);
const text = result.response.text();
return {
content: [
{
type: "text",
text: text,
},
],
};
}
default:
throw new Error(`Unknown tool: ${name}`);
}
} catch (error) {
return {
content: [
{
type: "text",
text: `Error: ${error.message}`,
},
],
isError: true,
};
}
});
// Start server
async function main() {
const transport = new StdioServerTransport();
await server.connect(transport);
console.error("Gemini MCP Server running on stdio");
}
main().catch((error) => {
console.error("Fatal error:", error);
process.exit(1);
});