webmachinelearning/webmcp

🤖 WebMCP

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Summary Information

Updated 26 minutes ago
Added to GitGenius on September 17th, 2026
Created on August 5th, 2025
Open Issues & Pull Requests: 130 (+0)
GitHub issues: Enabled
Number of forks: 275
Total Stargazers: 4,118 (+0)
Total Subscribers: 91 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 23.2 hours
Mean response time: 6.8 days
90th percentile: 14.1 days
Tracked items: 171

Most active contributors

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How this project is maintained

About 16% of issues opened in the past year have never received a reply. 72% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 48% of tracked open issues have had no activity in three months. Only 40% of issues opened in the past year have been closed. Three people close 80% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 120
New in 7 days: 1
Closed in 7 days: 4
Avg open age: 168 days
Stale 30+ days: 69
Stale 90+ days: 56

Recent activity

Opened in 7 days: 1
Closed in 7 days: 4
Comments in 7 days: 0
Events in 7 days: 1

Top labels

  • backlog (16)
  • declarative (12)
  • Agenda+ (7)
  • i18n-tracker (5)
  • security-tracker (5)
  • a11y-tracker (4)
  • developer feedback (1)
  • enhancement (1)

Detailed Description

WebMCP is a specification that allows web developers to expose JavaScript functions and HTML form elements as tools with natural language descriptions and structured schemas for AI agent consumption.

WebMCP addresses the limitations of backend integrations for interactive web applications. When AI agents interact with services through traditional backend APIs, they bypass the web UI, lose user context, and require developers to replicate authentication and state on separate servers. WebMCP solves this by letting developers define tools directly in browser pages using JavaScript or HTML forms. Agents can then invoke these tools while maintaining access to the page's UI and shared context, enabling more reliable and direct interaction with web content originally designed for human users.

Developers should choose WebMCP when building web applications that benefit from AI agent interaction while preserving the user's visual experience and application state. It suits scenarios where agents need to actuate web content cooperatively with users rather than through separate backend servers. The project provides TypeScript type definitions through an npm package and documents implementation status across different browsers and agents, along with best practices for designing effective tools.

The project maintains active specification development with regular updates to the core documentation and implementation guidance. The team engages with browser and agent platform developers to track and improve compatibility across different environments. Development focuses on establishing WebMCP as a practical standard for in-browser agent tooling rather than on rapid feature expansion.