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302AI BrowserUse MCP Server

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by 302ai
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Hybrid

🤖 302AI BrowserUse MCP Server🚀✨

Previews

Here are some usage examples

Here is the list of supported tools

Related MCP server: MCP Web Research Server

✨ Features ✨

  • 🔧 Dynamic Loading - Automatically update tool list from remote server.

  • 🌐 Multi modes supported, you can use stdin mode locally, or host it as a remote HTTP server

🚀 Tool List

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "302ai-browser-use-mcp": {
      "command": "npx",
      "args": ["-y", "@302ai/browser-use-mcp"],
      "env": {
        "302AI_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

To use with Cherry Studio, add the server config:

{
  "mcpServers": {
    "Li2ZXXJkvhAALyKOFeO4N": {
      "name": "302ai-browser-use-mcp",
      "description": "",
      "isActive": true,
      "registryUrl": "",
      "command": "npx",
      "args": [
        "-y",
        "@302ai/browser-use-mcp"
      ],
      "env": {
        "302AI_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

To use with ChatWise, copy the following content to clipboard

{
  "mcpServers": {
    "302ai-sandbox-mcp": {
      "command": "npx",
      "args": ["-y", "@302ai/browser-use-mcp"],
      "env": {
        "302AI_API_KEY": "YOUR_API_KEY_HERE"
      }
    }
  }
}

Go to Settings -> Tools -> Add button -> Select Import from Clipboard

Find Your 302AI_API_KEY here

Using Tutorials

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

✨ About 302.AI ✨

302.AI is an enterprise-oriented AI application platform that offers pay-as-you-go services, ready-to-use solutions, and an open-source ecosystem.✨

  1. 🧠 Integrates the latest and most comprehensive AI capabilities and brands, including but not limited to language models, image models, voice models, and video models.

  2. 🚀 Develops deep applications based on foundation models - we develop real AI products, not just simple chatbots

  3. 💰 Zero monthly fee, all features are pay-per-use, fully open, achieving truly low barriers with high potential.

  4. 🛠 Powerful management backend for teams and SMEs - one person manages, many people use.

  5. 🔗 All AI capabilities provide API access, all tools are open source and customizable (in progress).

  6. 💡 Strong development team, launching 2-3 new applications weekly, products updated daily. Developers interested in joining are welcome to contact us.

Available Tools

2 tools
createBrowserAgentTaskA

Create a browser agent task, and return the task id. This agent can handle continuous complex tasks, and you do not need to break down the tasks. Just input them directly. Clearly return the task_id to the user for use in the next request.

ParametersJSON Schema
NameRequiredDescriptionDefault
taskYesThe task that you want to execute, natural language.

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. Describes creation and return of task_id, and that agent handles continuous complex tasks. Does not disclose potential side effects, authentication needs, or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each earning its place: purpose, capability note, and output instruction. No redundant phrasing, front-loaded with key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given simple tool with one parameter, no output schema, and sibling tool, description sufficiently covers creation and follow-up usage. Lacks details on error handling or timeouts, but adequate for complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage with a single 'task' parameter described as natural language. The description mildly reinforces this ('Just input them directly') but adds no extra semantic detail beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Create a browser agent task' with verb+resource, and distinguishes from sibling tool getBrowserAgentTaskResult which retrieves results. Emphasizes handling of complex tasks without need for breakdown.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'you do not need to break down the tasks. Just input them directly,' providing clear when-to-use guidance. Also indicates to return task_id for use with sibling tool, but lacks explicit when-not-to-use or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

getBrowserAgentTaskResultA

Get the result of the browser agent task. If no results are obtained, clearly return the task_id to the user for use in the next request.

ParametersJSON Schema
NameRequiredDescriptionDefault
task_idYesThe task id that you want to get the result.

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It does not disclose key traits like polling behavior, idempotency, or error states. The note about returning task_id is an instruction to the agent, not a disclosure of tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose, and no superfluous wording. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple getter tool with one parameter and no output schema, the description covers the core action and provides a fallback instruction. It could mention that results may be pending if the task is still running, but overall adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'task_id' is fully described in the schema ('The task id that you want to get the result.'). The description adds no extra meaning, but schema coverage is 100%, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool's action: 'Get the result of the browser agent task.' The sibling tool 'createBrowserAgentTask' indicates creation, so this retrieval tool is distinct and well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Includes explicit guidance on handling no results: 'If no results are obtained, clearly return the task_id to the user for use in the next request.' While it doesn't mention when to use versus the sibling, the context implies use after creation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: one creates a task, the other retrieves its result. There is no overlap or ambiguity.

Naming Consistency4/5

Both tools use camelCase and follow a verb_noun pattern, but one ends with 'Task' and the other with 'TaskResult', introducing minor inconsistency. Still understandable.

Tool Count3/5

With only 2 tools, the server feels minimal. While it may suffice for the specific purpose of managing browser agent tasks, it is on the low end of reasonable scope.

Completeness2/5

The tool set covers creation and result retrieval, but lacks any management operations (e.g., list, cancel, retry). This limits the agent's ability to handle errors or task lifecycles.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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