Mastra.ai MCP Agent

# github
.github

# configurations
.idea
.vscode

# crawlee and apify storage folders
apify_storage
crawlee_storage
storage

# installed files
node_modules

# git folder
.git

# dist folder
dist

root = true

[*]
indent_style = space
indent_size = 4
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
end_of_line = lf

{
    "root": true,
    "env": {
        "es2022": true,  // Update from es2020
        "node": true
    },
    "extends": [
        "@apify/eslint-config-ts"
    ],
    "parserOptions": {
        "project": "./tsconfig.json",
        "ecmaVersion": 2022  // Match ES2022
    },
    "ignorePatterns": [
        "node_modules",
        "dist",
        "**/*.d.ts"
    ],
    "rules": {
        "@typescript-eslint/no-unused-vars": ["error"],  // Enforce unused vars
        "import/order": ["error", { "alphabetize": { "order": "asc" } }],  // Sort imports
        "@typescript-eslint/space-before-function-paren": "off", // Disable the invalid rule
        "space-before-function-paren": ["error", "always"]     // Use ESLint’s rule instead
    }
}

# Actor local input
input.json

# This file tells Git which files shouldn't be added to source control

.idea
.vscode
storage
apify_storage
crawlee_storage
node_modules
dist
tsconfig.tsbuildinfo

# Added by Apify CLI
.venv

{
  "tabWidth": 4,
  "singleQuote": true,
  "semi": true
}

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{
	"name": "actor-mastra-mcp",
	"version": "0.0.1",
	"type": "module",
	"description": "Mastra AI Agent with Apify MCP Server.",
	"engines": {
		"node": ">=18.0.0"
	},
	"dependencies": {
		"@ai-sdk/openai": "^1.2.5",
		"@mastra/core": "^0.4.4",
		"@mastra/mcp": "^0.3.5",
		"apify": "^3.3.2",
		"exit-hook": "^4.0.0",
		"mastra": "^0.2.8",
		"zod": "^3.24.2"
	},
	"devDependencies": {
		"@apify/eslint-config-ts": "^0.3.0",
		"@apify/tsconfig": "^0.1.0",
		"@types/json-schema": "^7.0.15",
		"@types/node": "^22.13.10",
		"@typescript-eslint/eslint-plugin": "^8.26.1",
		"@typescript-eslint/parser": "^8.26.1",
		"eslint": "^8.57.1",
		"prettier": "^3.5.3",
		"tsx": "^4.19.3",
		"typescript": "^5.8.2"
	},
	"scripts": {
		"start": "npm run start:dev",
		"start:prod": "node dist/main.js",
		"start:dev": "tsx src/main.ts",
		"build": "tsc",
		"test": "echo \"Error: oops, the Actor has no tests yet, sad!\" && exit 1",
		"format": "prettier --write \"src/**/*.{ts,js,json}\" && eslint ./src --ext .ts --fix",
		"lint": "eslint ./src --ext .ts",
        "lint:fix": "eslint ./src --ext .ts --fix"
	},
	"author": "It's not you it's me",
	"license": "ISC"
}

{
    "extends": "@apify/tsconfig",
    "compilerOptions": {
        "module": "NodeNext",
        "moduleResolution": "NodeNext",
        "target": "ES2022",
        "outDir": "dist",
        "skipLibCheck": true,
        "strict": true,              // Enable all strict options
        "noUnusedLocals": true,      // Catch unused variables
        "lib": []                    // Remove DOM unless needed; Node globals are sufficient
    },
    "include": [
        "./src/**/*"
    ]
}

# Specify the base Docker image. You can read more about
# the available images at https://docs.apify.com/sdk/js/docs/guides/docker-images
# You can also use any other image from Docker Hub.
FROM apify/actor-node:22 AS builder

# Copy just package.json and package-lock.json
# to speed up the build using Docker layer cache.
COPY package*.json ./

# Install all dependencies. Don't audit to speed up the installation.
RUN npm install --include=dev --audit=false

# Next, copy the source files using the user set
# in the base image.
COPY . ./

# Install all dependencies and build the project.
# Don't audit to speed up the installation.
RUN npm run build

# Create final image
FROM apify/actor-node:22

# Create and run as a non-root user.
RUN adduser -h /home/apify -D apify

# Copy just package.json and package-lock.json
# to speed up the build using Docker layer cache.
COPY package*.json ./

# Install NPM packages, skip optional and development dependencies to
# keep the image small. Avoid logging too much and print the dependency
# tree for debugging
RUN npm --quiet set progress=false \
    && npm install --omit=dev --omit=optional \
    && echo "Installed NPM packages:" \
    && (npm list --omit=dev --all || true) \
    && echo "Node.js version:" \
    && node --version \
    && echo "NPM version:" \
    && npm --version \
    && rm -r ~/.npm

# Copy built JS files from builder image
COPY --chown=apify --from=builder /usr/src/app/dist ./dist

# Next, copy the remaining files and directories with the source code.
# Since we do this after NPM install, quick build will be really fast
# for most source file changes.
COPY --chown=apify . ./

USER apify

# Run the image.
CMD npm run start:prod --silent

{
	"actorSpecification": 1,
	"name": "actor-mastra-mcp-agent",
	"title": "Mastra MCP agent",
	"description": "Mastra MCP agent",
	"version": "0.0",
	"buildTag": "latest",
	"storages": {
		"dataset": "./dataset_schema.json"
	},
	"meta": {
		"templateId": "ts-mastraai"
	},
	"input": "./input_schema.json",
	"dockerfile": "./Dockerfile"
}

{
  "actorSpecification": 1,
  "views": {
    "overview": {
      "title": "Overview",
      "transformation": {
        "fields": ["prompt", "response"]
      },
      "display": {
        "component": "table",
        "properties": {
          "prompt": {
            "label": "Prompt",
            "format": "text"
          },
          "response": {
            "label": "Response",
            "format": "text"
          }
        }
      }
    }
  }
}

{
  "title": "Mastra Agent TypeScript",
  "type": "object",
  "schemaVersion": 1,
  "properties": {
    "prompt": {
      "title": "Prompt",
      "type": "string",
      "description": "Prompt for the agent.",
      "editor": "textfield",
      "prefill": "Analyze the posts of the @openai and @googledeepmind and summarize me current trends in the AI."
    },
    "agentName": {
      "title": "Agent name",
      "type": "string",
      "description": "Name of the agent.",
      "editor": "textfield",
      "default": "Helpful Assistant Agent"
    },
    "agentInstructions": {
      "title": "Agent instructions",
      "type": "string",
      "description": "Instructions for the agent. Defines who the agent is and what it does.",
      "editor": "textarea",
      "default": "You are a helpful assistant who aims to help users with their questions and tasks. You provide clear, accurate information and guidance while maintaining a friendly and professional attitude."
    },
    "modelName": {
      "title": "OpenAI model",
      "type": "string",
      "description": "The OpenAI model to use. Currently supported models are gpt-4o and gpt-4o-mini.",
      "enum": [
        "gpt-4o",
        "gpt-4o-mini"
      ],
      "default": "gpt-4o-mini",
      "prefill": "gpt-4o-mini"
    },
    "mcpUrl": {
      "title": "MCP Server URL",
      "type": "string",
      "description": "The URL of the MCP Server to use.",
      "editor": "textfield",
      "default": "https://actors-mcp-server.apify.actor",
      "prefill": "https://actors-mcp-server.apify.actor"
    },
    "actors": {
      "title": "Actors included",
      "type": "array",
      "editor": "stringList",
      "description": "List of Apify Actor names to be available to the agent.",
      "prefill": [
          "clockworks/free-tiktok-scraper"
       ],
       "default": []
    },
    "toolTimeout": {
      "title": "MCP tool call timeout (s)",
      "type": "integer",
      "description": "Maximum time in seconds to wait for a tool call to complete.",
       "default": 300
    },
    "maxSteps": {
      "title": "Maximum steps for tool calls",
      "type": "integer",
      "description": "Controls the maximum number of sequential LLM calls an agent can make",
      "default": 3
    },
    "debug": {
      "title": "Debug",
      "type": "boolean",
      "description": "If enabled, Actor provides detailed information with tool calls and reasoning.",
      "editor": "checkbox",
      "default": false
    }
  },
  "required": ["prompt", "modelName", "actors"]
}

{
    "actor-start": {
        "eventTitle": "Price for Actor start",
        "eventDescription": "Flat fee for starting an Actor run.",
        "eventPriceUsd": 0.1
    },
    "task-completed": {
        "eventTitle": "Price for completing the task",
        "eventDescription": "Flat fee for completing the task.",
        "eventPriceUsd": 0.4
    }
}

1export const MCP_SERVER_URL_BASE = process.env.MCP_SERVER_URL_BASE || 'https://actors-mcp-server.apify.actor';

1// Apify SDK - toolkit for building Apify Actors (Read more at https://docs.apify.com/sdk/js/)
2import { openai } from '@ai-sdk/openai';
3import { Agent } from '@mastra/core/agent';
4import { Actor, log, LogLevel } from 'apify';
5import { gracefulExit } from 'exit-hook';
6import { createMCPClient, startMCPServer, stopMCPServer } from './mcp.js';
7import { getApifyToken } from './utils.js';
8
9// this is an ESM project, and as such, it requires you to specify extensions in your relative imports
10// read more about this here: https://nodejs.org/docs/latest-v18.x/api/esm.html#mandatory-file-extensions
11// note that we need to use `.js` even when inside TS files
12// import { router } from './routes.js';
13
14// Actor input schema
15interface Input {
16    prompt: string;
17    agentName: string;
18    agentInstructions: string;
19    modelName: string;
20    debug: boolean;
21    actors: string[];
22    toolTimeout: number;
23    maxSteps: number;
24    mcpUrl: string;
25}
26
27async function main (): Promise<number> {
28    // The init() call configures the Actor for its environment. It's recommended to start every Actor with an init()
29    await Actor.init();
30
31    /**
32     * Actor code
33     */
34
35    // Charge for Actor start
36    await Actor.charge({ eventName: 'actor-start' });
37
38    // Handle input
39    const {
40        prompt,
41        agentName,
42        agentInstructions,
43        modelName,
44        debug = false,
45        mcpUrl,
46        actors,
47        toolTimeout,
48        maxSteps,
49    } = (await Actor.getInput()) as Input;
50    if (!prompt) throw new Error('An agent prompt is required.');
51    if (!actors || actors.length === 0) throw new Error('At least one Apify Actor name is required.');
52    if (debug) log.setLevel(LogLevel.DEBUG);
53
54    // Create an MCP server
55    const apifyToken = getApifyToken();
56    const timeoutMillis = toolTimeout * 1000;
57    const mcpClient = createMCPClient(mcpUrl, apifyToken, timeoutMillis);
58
59    let mcpRunId = '';
60    try {
61        mcpRunId = await startMCPServer(mcpUrl, apifyToken, actors);
62        // Connect to MCP server
63        log.info('Connecting to MCP server...');
64        await mcpClient.connect();
65
66        // Gracefully handle process exits
67        process.on('exit', async () => {
68            await mcpClient.disconnect();
69            await stopMCPServer(mcpRunId);
70        });
71        // Fetch tools
72        const tools = await mcpClient.tools();
73        log.debug(`Tools: ${JSON.stringify(tools)}`);
74
75        // Create the agent
76        log.debug(
77            `Creating agent: ${agentName} (${modelName}) with instructions: ${agentInstructions}`,
78        );
79        const agent = new Agent({
80            name: agentName,
81            instructions: agentInstructions,
82            model: openai(modelName),
83            tools,
84        });
85
86        // Enrich the query
87        const enrichedPrompt = `${prompt}\n\nCurrent date and time: ${new Date().toISOString()}`;
88        log.info(`Prompting the agent with the following query: ${enrichedPrompt}`);
89
90        // Query the agent and get the response
91        const response = await agent.generate(
92            [
93                {
94                    role: 'user',
95                    content: enrichedPrompt,
96                },
97            ],
98            {
99                maxSteps,
100                onStepFinish: (step: string) => {
101                    log.info('Step completed:', { message: step.slice(0, 100) });
102                },
103            },
104        );
105
106        log.info(`Agent response: ${response.text}`);
107        log.info(`Tokens used total: ${response.usage.totalTokens}`);
108        log.info(`Prompt tokens used: ${response.usage.promptTokens}`);
109        log.info(`Completion tokens used: ${response.usage.completionTokens}`);
110
111        // Charge for the task completion
112        log.info('Charging for task completion...');
113        await Actor.charge({ eventName: 'task-completed' });
114
115        // Push results into the dataset
116        log.info('Pushing results into the dataset...');
117        await Actor.pushData({
118            prompt: enrichedPrompt,
119            response: response.text,
120        });
121    } catch (error) {
122        log.error(
123            `Actor failed with error: ${error instanceof Error ? error.stack : error}`,
124        );
125
126        // Always disconnect when done
127        await mcpClient.disconnect();
128        if (mcpRunId) await stopMCPServer(mcpRunId);
129        await Actor.fail({
130            statusMessage: 'Actor failed with an error, see logs',
131            exit: false,
132        });
133        return 1;
134    }
135
136    // Always disconnect when done
137    await mcpClient.disconnect();
138    if (mcpRunId) await stopMCPServer(mcpRunId);
139
140    // Gracefully exit the Actor process. It's recommended to quit all Actors with an exit()
141    // do not call process.exit() to wait for async operations to complete
142    await Actor.exit({ exit: false });
143    return 0;
144}
145
146const exitCode = await main();
147gracefulExit(exitCode);

1import { MastraMCPClient } from '@mastra/mcp';
2import { ApifyClient, log } from 'apify';
3import { getApifyToken } from './utils.js';
4
5/**
6 * Starts the MCP server with optional Actor specification
7 * @param {string} mcpUrl - The MCP server URL
8 * @param {string} apifyToken - The Apify API token for authentication
9 * @param {string[]} [actors] - Optional array of Actor names to be included in the server
10 * @returns {Promise<string>} The run ID of the MCP server
11 */
12export async function startMCPServer (
13    mcpUrl: string,
14    apifyToken: string,
15    actors: string[],
16): Promise<string> {
17    const url = `${mcpUrl}?actors=${actors.join(',')}`;
18    log.info(`Starting MCP server with url: ${url}`);
19
20    const response = await fetch(url, {
21        headers: {
22            Authorization: `Bearer ${apifyToken}`,
23        },
24    });
25    const json = (await response.json()) as { data: { id: string } };
26    return json.data.id;
27}
28/**
29 * Stops the running MCP server
30 * @returns {Promise<void>}
31 */
32export async function stopMCPServer (runId: string): Promise<void> {
33    log.info('Stopping MCP server...');
34
35    const token = getApifyToken();
36    const apifyClient = new ApifyClient({ token });
37
38    const run = apifyClient.run(runId);
39    if ((await run.get())?.status === 'RUNNING') await run.abort();
40}
41
42/**
43 * Creates an MCP client instance
44 * @param {string} mcpUrl - The MCP server URL
45 * @param {string} apifyToken - The Apify API token for authentication
46 * @param {number} [timeout=300_000] - The timeout in milliseconds for the client
47 * @returns {MastraMCPClient} MCP client instance
48 */
49export function createMCPClient (
50    mcpUrl: string,
51    apifyToken: string,
52    timeout: number = 300_000,
53): MastraMCPClient {
54    return new MastraMCPClient({
55        name: 'apify-client',
56        server: {
57            url: new URL(`${mcpUrl}/sse`),
58            requestInit: {
59                headers: {
60                    Authorization: `Bearer ${apifyToken}`,
61                },
62            },
63            eventSourceInit: {
64                // The EventSource package augments EventSourceInit with a "fetch" parameter.
65                // You can use this to set additional headers on the outgoing request.
66                // Based on this example: https://github.com/modelcontextprotocol/typescript-sdk/issues/118
67                async fetch (input: Request | URL | string, init?: RequestInit) {
68                    const headers = new Headers(init?.headers || {});
69                    headers.set(
70                        'authorization',
71                        `Bearer ${process.env.APIFY_TOKEN}`,
72                    );
73                    return fetch(input, { ...init, headers });
74                },
75            },
76        },
77        timeout,
78    });
79}

1export function getApifyToken (): string {
2    if (!process.env.APIFY_TOKEN) {
3        throw new Error('APIFY_TOKEN environment variable must be set');
4    }
5    return process.env.APIFY_TOKEN;
6}

name: Deploy Actor to Apify

on:
  push:
    branches:
      - main

jobs:
  deploy-to-apify:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout sources
        uses: actions/checkout@v4

      - name: Set up Node.js
        uses: actions/setup-node@v4
        with:
          node-version: 22

      - name: Push to Apify
        uses: apify/push-actor-action@master
        with:
          token: ${{ secrets.APIFY_TOKEN }}