588 lines
21 KiB
Plaintext
588 lines
21 KiB
Plaintext
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// Enhanced MCP Tools for Systems Provisioning
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// Integrates with new API server, AI agents, and dashboard capabilities
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use anyhow::Result;
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use serde_json::{json, Value};
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use std::process::Command;
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use reqwest::Client;
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pub struct ProvisioningTools {
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client: Client,
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api_base_url: String,
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}
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impl ProvisioningTools {
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pub fn new(api_base_url: Option<String>) -> Self {
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Self {
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client: Client::new(),
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api_base_url: api_base_url.unwrap_or_else(|| "http://localhost:3000".to_string()),
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}
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}
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/// Execute provisioning command with enhanced capabilities
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pub async fn execute_provisioning_command(&self, args: &[&str]) -> Result<Value> {
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let output = Command::new("./core/nulib/provisioning")
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.args(args)
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.output()
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.map_err(|e| anyhow::anyhow!("Failed to execute command: {}", e))?;
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let stdout = String::from_utf8_lossy(&output.stdout);
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let stderr = String::from_utf8_lossy(&output.stderr);
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if output.status.success() {
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Ok(json!({
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"success": true,
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"stdout": stdout,
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"stderr": stderr,
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"exit_code": 0
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}))
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} else {
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Ok(json!({
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"success": false,
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"stdout": stdout,
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"stderr": stderr,
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"exit_code": output.status.code().unwrap_or(-1)
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}))
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}
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}
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/// Query infrastructure using AI-powered natural language
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pub async fn ai_query(&self, query: &str, context: Option<&str>) -> Result<Value> {
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let mut args = vec!["ai", "query", "--prompt", query];
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if let Some(ctx) = context {
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args.extend(&["--context", ctx]);
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}
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let output = Command::new("./core/nulib/provisioning")
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.args(&args)
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.output()
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.map_err(|e| ToolError::ExecutionError(format!("AI query failed: {}", e)))?;
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let result = String::from_utf8_lossy(&output.stdout);
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// Try to parse as JSON, fallback to plain text
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if let Ok(parsed) = serde_json::from_str::<Value>(&result) {
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Ok(parsed)
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} else {
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Ok(json!({
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"query": query,
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"response": result.trim(),
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"type": "natural_language_response"
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}))
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}
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}
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/// Get infrastructure status via API
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pub async fn get_infrastructure_status(&self) -> Result<Value> {
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let url = format!("{}/api/v1/query?target=infrastructure", self.api_base_url);
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match self.client.get(&url).send().await {
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Ok(response) => {
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if response.status().is_success() {
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let data = response.json::<Value>().await
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.map_err(|e| ToolError::ExecutionError(format!("Failed to parse response: {}", e)))?;
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Ok(data)
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} else {
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// Fallback to CLI command
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self.execute_provisioning_command(&["show", "infrastructure"]).await
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}
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}
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Err(_) => {
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// Fallback to CLI command
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self.execute_provisioning_command(&["show", "infrastructure"]).await
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}
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}
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}
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/// Get system metrics via API
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pub async fn get_system_metrics(&self, timerange: Option<&str>) -> Result<Value> {
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let timerange = timerange.unwrap_or("1h");
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let url = format!("{}/api/v1/metrics?timerange={}", self.api_base_url, timerange);
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match self.client.get(&url).send().await {
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Ok(response) => {
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if response.status().is_success() {
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let data = response.json::<Value>().await
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.map_err(|e| ToolError::ExecutionError(format!("Failed to parse metrics: {}", e)))?;
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Ok(data)
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} else {
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// Fallback to CLI command
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self.execute_provisioning_command(&["query", "metrics", "--since", timerange]).await
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}
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}
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Err(_) => {
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// Fallback to CLI command
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self.execute_provisioning_command(&["query", "metrics", "--since", timerange]).await
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}
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}
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}
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/// Get logs with filtering via API
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pub async fn get_logs(&self, level: Option<&str>, since: Option<&str>) -> Result<Value> {
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let level = level.unwrap_or("info");
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let since = since.unwrap_or("1h");
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let url = format!("{}/api/v1/logs?level={}&since={}", self.api_base_url, level, since);
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match self.client.get(&url).send().await {
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Ok(response) => {
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if response.status().is_success() {
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let data = response.json::<Value>().await
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.map_err(|e| ToolError::ExecutionError(format!("Failed to parse logs: {}", e)))?;
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Ok(data)
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} else {
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// Fallback to CLI command
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self.execute_provisioning_command(&["logs", "--level", level, "--since", since]).await
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}
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}
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Err(_) => {
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// Fallback to CLI command
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self.execute_provisioning_command(&["logs", "--level", level, "--since", since]).await
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}
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}
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}
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/// Start API server
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pub async fn start_api_server(&self, port: Option<u16>) -> Result<Value> {
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let port = port.unwrap_or(3000);
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let port_str = port.to_string();
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self.execute_provisioning_command(&["api", "start", "--port", &port_str, "--background"]).await
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}
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/// Get API server status
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pub async fn get_api_status(&self) -> Result<Value> {
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let url = format!("{}/health", self.api_base_url);
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match self.client.get(&url).send().await {
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Ok(response) => {
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let status = response.status();
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let data = response.json::<Value>().await
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.unwrap_or(json!({"status": "unknown"}));
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Ok(json!({
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"api_available": status.is_success(),
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"status_code": status.as_u16(),
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"data": data
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}))
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}
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Err(e) => {
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Ok(json!({
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"api_available": false,
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"error": e.to_string()
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}))
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}
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}
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}
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/// Create and start dashboard
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pub async fn create_dashboard(&self, template: Option<&str>, name: Option<&str>) -> Result<Value> {
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let template = template.unwrap_or("full");
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let name = name.unwrap_or("ai-dashboard");
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self.execute_provisioning_command(&["dashboard", "create", template, name]).await
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}
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/// Start existing dashboard
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pub async fn start_dashboard(&self, name: &str, port: Option<u16>) -> Result<Value> {
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let port = port.unwrap_or(8080);
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let port_str = port.to_string();
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self.execute_provisioning_command(&["dashboard", "start", name, &port_str]).await
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}
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/// Start AI agents
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pub async fn start_ai_agents(&self, agents: Option<Vec<&str>>) -> Result<Value> {
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let mut args = vec!["agents", "start"];
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if let Some(agent_list) = agents {
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args.push("--agents");
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args.push(&format!("[{}]", agent_list.join(", ")));
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}
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self.execute_provisioning_command(&args).await
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}
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/// Get AI agents status
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pub async fn get_agents_status(&self) -> Result<Value> {
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self.execute_provisioning_command(&["agents", "status"]).await
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}
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/// Create servers with configuration
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pub async fn create_servers(&self, config: &Value) -> Result<Value> {
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let template = config.get("template").and_then(|v| v.as_str()).unwrap_or("default");
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let count = config.get("count").and_then(|v| v.as_u64()).unwrap_or(1);
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let provider = config.get("provider").and_then(|v| v.as_str()).unwrap_or("local");
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let instance_type = config.get("instance_type").and_then(|v| v.as_str());
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let mut args = vec![
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"server", "create",
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"--template", template,
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"--count", &count.to_string(),
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"--provider", provider
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];
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if let Some(itype) = instance_type {
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args.extend(&["--instance-type", itype]);
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}
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self.execute_provisioning_command(&args).await
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}
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/// List servers
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pub async fn list_servers(&self, provider: Option<&str>) -> Result<Value> {
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let mut args = vec!["server", "list"];
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if let Some(p) = provider {
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args.extend(&["--provider", p]);
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}
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self.execute_provisioning_command(&args).await
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}
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/// Delete servers
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pub async fn delete_servers(&self, server_names: &[&str]) -> Result<Value> {
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let mut args = vec!["server", "delete"];
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args.extend(server_names);
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self.execute_provisioning_command(&args).await
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}
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/// Create Kubernetes cluster
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pub async fn create_cluster(&self, config: &Value) -> Result<Value> {
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let name = config.get("name").and_then(|v| v.as_str()).unwrap_or("k8s-cluster");
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let nodes = config.get("nodes").and_then(|v| v.as_u64()).unwrap_or(3);
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let provider = config.get("provider").and_then(|v| v.as_str()).unwrap_or("local");
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let args = vec![
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"cluster", "create",
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"--name", name,
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"--nodes", &nodes.to_string(),
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"--provider", provider
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];
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self.execute_provisioning_command(&args).await
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}
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/// Generate infrastructure from natural language description
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pub async fn generate_infrastructure(&self, description: &str, output_type: Option<&str>) -> Result<Value> {
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let output_type = output_type.unwrap_or("server");
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let args = vec![
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"ai", "template",
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"--prompt", description,
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"--template-type", output_type
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];
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self.execute_provisioning_command(&args).await
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}
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/// Get cost optimization recommendations
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pub async fn get_cost_optimization(&self) -> Result<Value> {
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self.ai_query("How can I reduce infrastructure costs and optimize spending?", None).await
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}
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/// Get security analysis
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pub async fn get_security_analysis(&self) -> Result<Value> {
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self.ai_query("Perform a security analysis of current infrastructure and identify threats", None).await
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}
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/// Get performance analysis
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pub async fn get_performance_analysis(&self) -> Result<Value> {
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self.ai_query("Analyze system performance and identify bottlenecks", None).await
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}
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/// Predict infrastructure issues
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pub async fn predict_issues(&self, timeframe: Option<&str>) -> Result<Value> {
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let timeframe = timeframe.unwrap_or("next week");
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let query = format!("Predict potential infrastructure issues for {}", timeframe);
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self.ai_query(&query, None).await
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}
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}
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// Tool definitions for MCP registration
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pub fn get_provisioning_tools() -> Vec<Tool> {
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vec![
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Tool {
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name: "execute_provisioning_command".to_string(),
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description: "Execute provisioning CLI commands with enhanced capabilities".to_string(),
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input_schema: json!({
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"type": "object",
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"properties": {
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"args": {
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"type": "array",
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"items": {"type": "string"},
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"description": "Command arguments to pass to provisioning CLI"
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}
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},
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"required": ["args"]
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})
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},
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Tool {
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name: "ai_query".to_string(),
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description: "Query infrastructure using AI-powered natural language processing".to_string(),
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input_schema: json!({
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"type": "object",
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"properties": {
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"query": {
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"type": "string",
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"description": "Natural language query about infrastructure"
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},
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"context": {
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"type": "string",
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"description": "Additional context for the query (optional)"
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}
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},
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"required": ["query"]
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})
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},
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Tool {
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name: "get_infrastructure_status".to_string(),
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description: "Get current infrastructure status via API or CLI".to_string(),
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input_schema: json!({
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"type": "object",
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"properties": {}
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})
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},
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Tool {
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name: "get_system_metrics".to_string(),
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description: "Retrieve system metrics for specified time range".to_string(),
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input_schema: json!({
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"type": "object",
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"properties": {
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"timerange": {
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"type": "string",
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"description": "Time range for metrics (e.g., '1h', '24h', '7d')",
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"default": "1h"
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}
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}
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})
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},
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Tool {
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name: "get_logs".to_string(),
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description: "Retrieve filtered logs from infrastructure".to_string(),
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input_schema: json!({
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"type": "object",
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"properties": {
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"level": {
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"type": "string",
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"description": "Log level filter (debug, info, warn, error)",
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"default": "info"
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},
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"since": {
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"type": "string",
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"description": "Time range for logs (e.g., '1h', '24h')",
|
||
|
|
"default": "1h"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "start_api_server".to_string(),
|
||
|
|
description: "Start the provisioning API server".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"port": {
|
||
|
|
"type": "integer",
|
||
|
|
"description": "Port number for API server",
|
||
|
|
"default": 3000
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "get_api_status".to_string(),
|
||
|
|
description: "Check API server availability and status".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "create_dashboard".to_string(),
|
||
|
|
description: "Create interactive dashboard using Marimo".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"template": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Dashboard template (monitoring, infrastructure, full, ai-insights)",
|
||
|
|
"default": "full"
|
||
|
|
},
|
||
|
|
"name": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Dashboard name",
|
||
|
|
"default": "ai-dashboard"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "start_dashboard".to_string(),
|
||
|
|
description: "Start existing dashboard server".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"name": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Dashboard name to start"
|
||
|
|
},
|
||
|
|
"port": {
|
||
|
|
"type": "integer",
|
||
|
|
"description": "Port number for dashboard",
|
||
|
|
"default": 8080
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"required": ["name"]
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "start_ai_agents".to_string(),
|
||
|
|
description: "Start AI agents for intelligent infrastructure monitoring".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"agents": {
|
||
|
|
"type": "array",
|
||
|
|
"items": {"type": "string"},
|
||
|
|
"description": "List of agents to start (pattern_detector, cost_optimizer, performance_analyzer, security_monitor, predictor, auto_healer)"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "get_agents_status".to_string(),
|
||
|
|
description: "Get status of all AI agents".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "create_servers".to_string(),
|
||
|
|
description: "Create servers with specified configuration".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"config": {
|
||
|
|
"type": "object",
|
||
|
|
"description": "Server configuration",
|
||
|
|
"properties": {
|
||
|
|
"template": {"type": "string", "default": "default"},
|
||
|
|
"count": {"type": "integer", "default": 1},
|
||
|
|
"provider": {"type": "string", "default": "local"},
|
||
|
|
"instance_type": {"type": "string"}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"required": ["config"]
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "list_servers".to_string(),
|
||
|
|
description: "List all servers, optionally filtered by provider".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"provider": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Filter by provider (aws, gcp, azure, local)"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "delete_servers".to_string(),
|
||
|
|
description: "Delete specified servers".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"server_names": {
|
||
|
|
"type": "array",
|
||
|
|
"items": {"type": "string"},
|
||
|
|
"description": "Names of servers to delete"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"required": ["server_names"]
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "create_cluster".to_string(),
|
||
|
|
description: "Create Kubernetes cluster with specified configuration".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"config": {
|
||
|
|
"type": "object",
|
||
|
|
"description": "Cluster configuration",
|
||
|
|
"properties": {
|
||
|
|
"name": {"type": "string", "default": "k8s-cluster"},
|
||
|
|
"nodes": {"type": "integer", "default": 3},
|
||
|
|
"provider": {"type": "string", "default": "local"}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"required": ["config"]
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "generate_infrastructure".to_string(),
|
||
|
|
description: "Generate infrastructure configuration from natural language description".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"description": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Natural language description of desired infrastructure"
|
||
|
|
},
|
||
|
|
"output_type": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Type of output (server, cluster, taskserv)",
|
||
|
|
"default": "server"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"required": ["description"]
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "get_cost_optimization".to_string(),
|
||
|
|
description: "Get AI-powered cost optimization recommendations".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "get_security_analysis".to_string(),
|
||
|
|
description: "Get comprehensive security analysis using AI agents".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "get_performance_analysis".to_string(),
|
||
|
|
description: "Get detailed performance analysis and bottleneck identification".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {}
|
||
|
|
})
|
||
|
|
},
|
||
|
|
Tool {
|
||
|
|
name: "predict_issues".to_string(),
|
||
|
|
description: "Predict potential infrastructure issues using AI".to_string(),
|
||
|
|
input_schema: json!({
|
||
|
|
"type": "object",
|
||
|
|
"properties": {
|
||
|
|
"timeframe": {
|
||
|
|
"type": "string",
|
||
|
|
"description": "Prediction timeframe (e.g., 'next week', 'next month')",
|
||
|
|
"default": "next week"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
})
|
||
|
|
}
|
||
|
|
]
|
||
|
|
}
|