اتصال سرورهای MCP به آشا

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import OpenAI from "openai";

const MODEL = "~anthropic/claude-sonnet-latest";

const openai = new OpenAI({
  baseURL: "https://app.asha-ai.ir/v1/",
  apiKey: process.env.ASHA_API_KEY!,
});

const mcp = new Client({ name: "asha-mcp-client", version: "1.0.0" });
await mcp.connect(new StdioClientTransport({
  command: "npx",
  args: ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"],
}));

const { tools } = await mcp.listTools();

const toOpenAITool = (t: any) => ({
  type: "function",
  function: {
    name: t.name,
    description: t.description,
    parameters: t.inputSchema,
  },
});

const messages: any[] = [
  { role: "user", content: "List the files in my folder." },
];
const functionDefs = tools.map(toOpenAITool);

let assistant = (
  await openai.chat.completions.create({ model: MODEL, messages, tools: functionDefs })
).choices[0].message;
messages.push(assistant);

while (assistant.tool_calls?.length) {
  for (const call of assistant.tool_calls) {
    const result = await mcp.callTool({
      name: call.function.name,
      arguments: JSON.parse(call.function.arguments ?? "{}"),
    });
    messages.push({
      role: "tool",
      tool_call_id: call.id,
      content: result.content?.[0]?.text ?? "",
    });
  }

  assistant = (
    await openai.chat.completions.create({ model: MODEL, messages, tools: functionDefs })
  ).choices[0].message;
  messages.push(assistant);
}

console.log(assistant.content);

import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import OpenAI from "openai";

const MODEL = "~anthropic/claude-sonnet-latest";

const openai = new OpenAI({
  baseURL: "https://app.asha-ai.ir/v1/",
  apiKey: process.env.ASHA_API_KEY,
});

const mcp = new Client({ name: "asha-mcp-client", version: "1.0.0" });
await mcp.connect(new StdioClientTransport({
  command: "npx",
  args: ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"],
}));

const { tools } = await mcp.listTools();

const toOpenAITool = (t) => ({
  type: "function",
  function: {
    name: t.name,
    description: t.description,
    parameters: t.inputSchema,
  },
});

const messages = [{ role: "user", content: "List the files in my folder." }];
const functionDefs = tools.map(toOpenAITool);

let assistant = (
  await openai.chat.completions.create({ model: MODEL, messages, tools: functionDefs })
).choices[0].message;
messages.push(assistant);

while (assistant.tool_calls?.length) {
  for (const call of assistant.tool_calls) {
    const result = await mcp.callTool({
      name: call.function.name,
      arguments: JSON.parse(call.function.arguments ?? "{}"),
    });
    messages.push({
      role: "tool",
      tool_call_id: call.id,
      content: result.content?.[0]?.text ?? "",
    });
  }

  assistant = (
    await openai.chat.completions.create({ model: MODEL, messages, tools: functionDefs })
  ).choices[0].message;
  messages.push(assistant);
}

console.log(assistant.content);

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"log"
	"os"
	"time"

	"github.com/mark3labs/mcp-go/client"
	"github.com/mark3labs/mcp-go/mcp"
	openai "github.com/sashabaranov/go-openai"
)

const model = "~anthropic/claude-sonnet-latest"

func main() {
	ctx, cancel := context.WithTimeout(context.Background(), 5*time.Minute)
	defer cancel()

	mcpClient, err := client.NewStdioMCPClient(
		"npx", nil,
		"-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir",
	)
	if err != nil {
		log.Fatal(err)
	}
	defer mcpClient.Close()

	if _, err := mcpClient.Initialize(ctx, mcp.InitializeRequest{}); err != nil {
		log.Fatal(err)
	}

	listed, err := mcpClient.ListTools(ctx, mcp.ListToolsRequest{})
	if err != nil {
		log.Fatal(err)
	}
	for _, t := range listed.Tools {
		fmt.Printf("- %s: %sn", t.Name, t.Description)
	}

	tools := make([]openai.Tool, 0, len(listed.Tools))
	for _, t := range listed.Tools {
		schemaJSON, _ := json.Marshal(t.InputSchema)
		var schema any
		_ = json.Unmarshal(schemaJSON, &schema)
		tools = append(tools, openai.Tool{
			Type: openai.ToolTypeFunction,
			Function: &openai.FunctionDefinition{
				Name:        t.Name,
				Description: t.Description,
				Parameters:  schema,
			},
		})
	}

	ai := openai.NewClientWithConfig(openai.DefaultConfig(os.Getenv("ASHA_API_KEY")))
	ai.BaseURL = "https://app.asha-ai.ir/v1"

	messages := []openai.ChatCompletionMessage{
		{Role: openai.ChatMessageRoleUser, Content: "List the files in my folder."},
	}

	next := func() (openai.ChatCompletionMessage, error) {
		reply, err := ai.CreateChatCompletion(ctx, openai.ChatCompletionRequest{
			Model:      model,
			Messages:   messages,
			Tools:      tools,
			ToolChoice: "auto",
		})
		if err != nil {
			return openai.ChatCompletionMessage{}, err
		}
		assistant := reply.Choices[0].Message
		messages = append(messages, assistant)
		return assistant, nil
	}

	assistant, err := next()
	if err != nil {
		log.Fatal(err)
	}

	for len(assistant.ToolCalls) > 0 {
		for _, call := range assistant.ToolCalls {
			args := map[string]any{}
			_ = json.Unmarshal([]byte(call.Function.Arguments), &args)
			res, err := mcpClient.CallTool(ctx, mcp.CallToolRequest{
				Params: mcp.CallToolParams{
					Name:      call.Function.Name,
					Arguments: args,
				},
			})
			if err != nil {
				log.Fatal(err)
			}
			text := ""
			for _, c := range res.Content {
				if tc, ok := c.(mcp.TextContent); ok {
					text += tc.Text
				}
			}
			messages = append(messages, openai.ChatCompletionMessage{
				Role:       openai.ChatMessageRoleTool,
				ToolCallID: call.ID,
				Content:    text,
			})
		}
		assistant, err = next()
		if err != nil {
			log.Fatal(err)
		}
	}

	fmt.Println(assistant.Content)
}

<?php

require 'vendor/autoload.php';

use McpClient;
use McpClientTransportStdioTransport;
use McpSchemaContentTextContent;
use OpenAI;

$model = '~anthropic/claude-sonnet-latest';

$asha = OpenAI::factory()
    ->withApiKey($_ENV['ASHA_API_KEY'])
    ->withBaseUri('https://app.asha-ai.ir/v1/')
    ->make();

$mcp = Client::builder()
    ->setClientInfo('asha-mcp-client', '1.0.0')
    ->build();

$mcp->connect(new StdioTransport(
    command: 'npx',
    args: ['-y', '@modelcontextprotocol/server-filesystem', '/path/to/dir'],
));

$toolsResult = $mcp->listTools();

$tools = array_map(static function (object $tool): array {
    return [
        'type' => 'function',
        'function' => [
            'name' => $tool->name,
            'description' => $tool->description,
            'parameters' => $tool->inputSchema,
        ],
    ];
}, $toolsResult->tools);

$messages = [
    ['role' => 'user', 'content' => 'List the files in my folder.'],
];

$completion = $asha->chat()->create([
    'model' => $model,
    'messages' => $messages,
    'tools' => $tools,
]);

$assistant = $completion->choices[0]->message;
$messages[] = [
    'role' => 'assistant',
    'content' => $assistant->content,
    'tool_calls' => $assistant->toolCalls,
];

while (!empty($assistant->toolCalls)) {
    foreach ($assistant->toolCalls as $call) {
        $result = $mcp->callTool(
            $call->function->name,
            json_decode($call->function->arguments ?? '{}', true),
        );
        $text = '';
        foreach ($result->content as $content) {
            if ($content instanceof TextContent) {
                $text .= $content->text;
            }
        }
        $messages[] = [
            'role' => 'tool',
            'tool_call_id' => $call->id,
            'content' => $text,
        ];
    }

    $completion = $asha->chat()->create([
        'model' => $model,
        'messages' => $messages,
        'tools' => $tools,
    ]);
    $assistant = $completion->choices[0]->message;
    $messages[] = [
        'role' => 'assistant',
        'content' => $assistant->content,
        'tool_calls' => $assistant->toolCalls,
    ];
}

echo $assistant->content . PHP_EOL;

$mcp->disconnect();

# ---- Request 1: model asks to call a tool (finish_reason: tool_calls) ----
curl https://app.asha-ai.ir/v1/chat/completions 
  -H "Authorization: Bearer $ASHA_API_KEY" 
  -H "Content-Type: application/json" 
  -d '{
    "model": "~anthropic/claude-sonnet-latest",
    "messages": [
      { "role": "user", "content": "List the files in my folder." }
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "list_directory",
          "description": "List the files in a directory",
          "parameters": {
            "type": "object",
            "properties": { "path": { "type": "string" } }
          }
        }
      }
    ]
  }'

# ---- Request 2: append role:tool result, get the final answer ----
curl https://app.asha-ai.ir/v1/chat/completions 
  -H "Authorization: Bearer $ASHA_API_KEY" 
  -H "Content-Type: application/json" 
  -d '{
    "model": "~anthropic/claude-sonnet-latest",
    "messages": [
      { "role": "user", "content": "List the files in my folder." },
      {
        "role": "assistant",
        "content": null,
        "tool_calls": [
          {
            "id": "call_abc123",
            "type": "function",
            "function": {
              "name": "list_directory",
              "arguments": "{"path":"/home/user"}"
            }
          }
        ]
      },
      {
        "role": "tool",
        "tool_call_id": "call_abc123",
        "content": "README.mdnsrc/n"
      }
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "list_directory",
          "description": "List the files in a directory",
          "parameters": {
            "type": "object",
            "properties": { "path": { "type": "string" } }
          }
        }
      }
    ]
  }'