AI & Machine Learning

webrun.ai

WebRun is an AI platform that deploys autonomous agents to handle daily business operations within existing tools, at a low cost per task.

2 endpoints12 known toolsFirst detected August 8, 2026Last detected August 8, 2026

ENDPOINT 1

https://api.webrun.ai/mcp

No auth detected

MCP server metadata

Name: webrun-browser
Version: 2.0.0

Capabilities

tools

Server instructions

WebRun drives a real Chrome browser in the cloud. Use browser_task for one-off tasks (creates a session, runs, auto-terminates). For multi-step work: create_session, then send_task per task, then terminate_session. After starting a task, poll get_task_status; if it reports awaiting_input, answer with guardrail_response. screenshot and pull_debug inspect a live session. Docs: https://docs.webrun.ai

Known tools 12

browser_task

Execute a browser automation task in a real Chrome browser running in a WebRun cloud environment (docs.webrun.ai).

Potential side effects

create_session

Create a persistent session in a real Chrome browser running in a WebRun cloud environment (docs.webrun.ai), for multi-step workflows.

Potential side effects

send_task

Send a new task to an existing browser session (from create_session).

Potential side effects

pause_session_task

Pause the task currently running in a browser session.

Inferred read-only

resume_session_task

Resume a previously paused task in a browser session.

Inferred read-only

stop_session_task

Cancel the task currently running in a browser session, keeping the session alive for new tasks.

Inferred read-only

terminate_session

End a browser session and free its resources.

Inferred read-only

guardrail_response

Respond to a guardrail trigger when the browser agent needs human input (credentials, clarification, approval).

Inferred read-only

get_task_status

Check the status of a task previously started in a browser session.

Inferred read-only

screenshot

Capture a screenshot of the current browser page in an active session.

Inferred read-only

list_sessions

List all active browser sessions for this account.

Inferred read-only

list_environments

List available browser environments (persistent profiles) for this account.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.webrun-browser]
url = "https://api.webrun.ai/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "webrun-browser": {
      "type": "http",
      "url": "https://api.webrun.ai/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: webrun-browser
Remote MCP URL: https://api.webrun.ai/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "webrun-browser": {
      "url": "https://api.webrun.ai/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "webrun-browser": {
      "type": "http",
      "url": "https://api.webrun.ai/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "webrun-browser",
  "transport": "streamable-http",
  "url": "https://api.webrun.ai/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

ENDPOINT 2

https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx

Auth required

Known tools 0

No tool metadata was available in the registry cache.

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.webrun-ai]
url = "https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx"
enabled = true
bearer_token_env_var = "MCP_BEARER_TOKEN"

Authentication is required. Replace the placeholder locally and never commit a secret.

Claude Code

.mcp.json

{
  "mcpServers": {
    "webrun-ai": {
      "type": "http",
      "url": "https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx",
      "headers": {
        "Authorization": "Bearer YOUR_BEARER_TOKEN"
      }
    }
  }
}

Authentication is required. Replace the placeholder locally and never commit a secret.

Claude Desktop

Settings → Connectors → Add custom connector

Name: webrun-ai
Remote MCP URL: https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx

Add the URL as a custom connector, then complete its supported authorization flow. Claude Desktop remote connectors are configured in the UI.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "webrun-ai": {
      "url": "https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx",
      "headers": {
        "Authorization": "Bearer YOUR_BEARER_TOKEN"
      }
    }
  }
}

Authentication is required. Replace the placeholder locally and never commit a secret.

Visual Studio Code

.vscode/mcp.json

{
  "servers": {
    "webrun-ai": {
      "type": "http",
      "url": "https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx",
      "headers": {
        "Authorization": "Bearer ${input:mcp-token}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "mcp-token",
      "description": "webrun-ai bearer token",
      "password": true
    }
  ]
}

Authentication is required. Replace the placeholder locally and never commit a secret.

Generic MCP

Client-specific MCP configuration

{
  "name": "webrun-ai",
  "transport": "streamable-http",
  "url": "https://api.webrun.ai/mcp/wr_xxxxxxxxxxxx",
  "headers": {
    "Authorization": "Bearer YOUR_BEARER_TOKEN"
  }
}

Authentication is required. Replace the placeholder locally and never commit a secret.

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Loading Trust v2 evidence…

Checking the associated registrable domain. The BuiltWith key remains server-side.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.