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  3. Doubleoh MCP
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Health: ActiveRecent health check succeeded.Last checked 10/14/2026, 7:17:03 PM

Doubleoh MCP

InstallableWe know how to install it, but have not yet seen it complete a handshake. User RatingsBe the first to rate and review this MCP server!
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website
mcpagent-skillsbrowser-automationhuman-in-the-loopaudit

Helps agents reuse approved browser fixes as bounded skills, with human intervention and audit records when needed.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

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We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Configure Environment Variables (API Keys, Tokens, Options):
Add required secrets below — values are included directly in the generated snippet so you can copy and paste with confidence.
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Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "doubleoh-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "doubleoh-mcp"
      ],
      "env": {
        "DOUBLEOH_API_KEY": "YOUR_VALUE_HERE",
        "DOUBLEOH_ADMIN_EMAIL": "YOUR_VALUE_HERE",
        "DOUBLEOH_ADMIN_PASSWORD": "YOUR_VALUE_HERE"
      }
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives💻 More in Developer Tools

Overview

The doubleoh-mcp MCP server gives agents access to DoubleOh’s reusable skills and human-assisted fix workflow. Agents can look up skills for a task and URL, request a fix when they reach a boundary, and report whether a learned skill worked. DoubleOh returns procedures with authority limits, while people handle credentials, approvals, and other steps requiring human control. Use it when agents need repeatable browser procedures with oversight and a record of interventions.

Use cases

•Reuse approved browser procedures across agents
•Request human help for blocked web tasks
•Record whether learned skills still work
•Keep audit records for agent interventions

Key features

•Task and URL-based skill lookup
•Human-assisted fix requests
•Bounded procedures with authority limits
•Skill success reporting
•Intervention audit records
•Agent Skills format support

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Doubleoh MCP.

Extracted Tool Capabilities
Task and URL-based skill lookup
Human-assisted fix requests
Bounded procedures with authority limits
Skill success reporting
Intervention audit records
Agent Skills format support

How Doubleoh MCP works

What doubleoh-mcp does

The doubleoh-mcp MCP server connects an MCP-capable agent to a self-hosted DoubleOh deployment. It exposes the main workflow for finding and learning procedures: retrieve skills relevant to a task and site, ask for help when the agent is blocked, and report whether a skill succeeded.

A successful fix is turned into a bounded skill rather than a raw interaction transcript. The resulting procedure contains numbered steps, a condition describing when the task is complete, and an authority statement. That statement identifies actions that still require a person and actions the agent must not take.

Skills are scoped to the customer and the site where they were learned. They use the documented Agent Skills format and can retire when they stop working. Each intervention also has an oversight record containing details such as who requested the fix, who intervened, the authority involved, and what the fleet learned.

How it works

An agent first calls skillsFor(task, { url }) to check whether DoubleOh already has a procedure for the current task and site. If the same obstacle is known, the learned skill can be returned without paging a person. Otherwise, requestFix({ url, task }) creates a fix request and provides a link for a person to take control of the agent’s live browser or desktop session.

The person completes the blocked step. Typed text is not recorded, so credentials and one-time codes remain with the person. A vision model then turns the recorded interaction into a procedure with explicit boundaries. The agent can call reportSkill(skill.name, worked) afterward so the skill library reflects whether the procedure was effective.

The doubleoh-mcp MCP server is intended for MCP-capable agents that need these three operations without adding a framework-specific adapter. The repository also mentions adapters for several agent frameworks, but those are separate integration paths.

Setup and configuration

The MCP package is published for use with npx doubleoh-mcp. It connects to a DoubleOh deployment, such as one started from the repository’s Docker Compose setup. Self-hosting requires Docker, at least 4 GB of memory, and an Anthropic key for the skill compiler. The initial image pull is approximately 5 GB.

For a local deployment, the documented startup flow copies .env.example to .env, starts the containers, and opens the application at http://localhost:3001. The administrator signs in with DOUBLEOH_ADMIN_EMAIL and DOUBLEOH_ADMIN_PASSWORD. The SDK example uses DOUBLEOH_API_KEY and a configurable baseUrl; MCP client configuration should provide equivalent access to the DoubleOh instance.

The repository states that configured model calls are the only traffic that leaves the local network. Deployment and configuration details, including external database and platform options, are maintained in the project documentation.

Tools and capabilities

The doubleoh-mcp MCP server provides these core operations:

  • skillsFor: find existing skills for a task and URL.
  • requestFix: reuse a known fix or request human intervention for an unresolved obstacle.
  • reportSkill: record whether a named skill worked.

The workflow supports public web targets by default. A native runtime can be used for an ERP, Windows application, or staging portal on a machine that can access it. That runtime makes one outbound connection and does not listen for inbound connections.

Limitations and notes

Public, loopback, private, and metadata addresses are restricted by default. A host must be allowlisted for use with a custom runtime. The material does not describe the MCP server’s complete transport or client-specific configuration, so connection details may depend on the MCP client and the DoubleOh deployment.

Human intervention remains necessary for actions outside a skill’s authority boundary. Credentials and one-time codes are not recorded, and the system retains an audit trail of interventions. The repository uses the Sustainable Use License for the self-hosted application, while the MCP package is listed as MIT-licensed. The Sustainable Use terms do not allow hosting the software as a service for others without a commercial license.

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
1
Stargazers on the source repository.
npm downloads
1.7k
Package downloads in the last 30 days.
Last commit
19d ago
Most recent push to the default branch.

Reviews

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Frequently Asked Questions about Doubleoh MCP

doubleoh-mcp is an MCP server that connects AI agents to a DoubleOh deployment and its reusable browser-task skills. Its main tools look up skills for a task and URL, request human help when an agent is blocked, and report whether a learned skill worked. Procedures include authority boundaries and interventions remain auditable.

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Technical Specs & Signals

Category💻Developer Tools
More technical detailsExpand ▾
TransportSTDIO
RuntimeNode.js
LicenseMIT
ClientsClaude Desktop, Cursor, Cline / VS Code, Windsurf, Claude Code, VS Code (GitHub Copilot), Zed, OpenAI Codex CLI, Gemini CLI, JetBrains AI Assistant, Roo Code, Continue, LM Studio
Last updatedOct 14, 2026
Views0
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
Last commit19d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 24, 2026
npm downloads1,716/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
44Quality signal: Fair · 44/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools15/30
Adoption & activity8/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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No high-severity advisories surfaced by our automated scan.

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Scanned 1h ago via OSV.dev · doubleoh-mcp (npm)

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