"How to scrape websites and format content in GitHub Markdown" matching MCP servers:

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP relay that adds a use_jev tool to every connected server, letting the Jev model autonomously select and execute tool calls while the calling model supplies any required text values. It enables agents to delegate multi-step tool use across all configured MCP servers through a single unified interface.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

Enables users to describe an LLM fine-tuning workload once and receive ranked, task-aware GPU recommendations across a dozen cloud providers based on required VRAM/FLOPs, cost, and runtime. It surfaces the cheapest, fastest, and balanced options through MCP so coding assistants can plan training hardware without manual price comparison.

Enables AI agents to analyze employee GitHub activity including PRs, code reviews, comments, and contributions across repositories with time-range filtering for performance assessment and impact analysis.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables AI coding agents and human managers to coordinate work on GitHub Projects v2 through 20 tools and 169 actions for autonomous task checkout, heartbeats, reviews, token budgets, PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines, backed by GitHub-native storage and MCP resources/prompts.

Enables AI agents and human managers to orchestrate GitHub-based project work by self-assigning tasks, coordinating swarms, tracking token budgets, generating PRDs, planning sprints, triaging issues, and materializing tasks as GitHub issues, milestones, and project views.

Turns GitHub Projects v2 into an agentic project-management layer where AI coding agents register, atomically claim and self-assign tasks, heartbeat, review each other's work products, and operate within token budgets. It also exposes 20 compound tools (169 actions) plus MCP resources, prompts, and sampling for AI-powered PRD generation, task breakdown, sprint planning, issue triage, and a PRD-to-issues pipeline, all stored natively in GitHub with no external infrastructure.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Enables AI coding agents and project managers to turn GitHub Projects v2 into an autonomous project management layer with task checkout, multi-agent swarms, PRD-to-issue pipelines, sprint planning, triage, and GitHub Actions/Releases/Branches support via 20 compound tools and 169 actions.

Enables AI agents to register, claim tasks atomically, coordinate via heartbeats, and submit work for review while human managers generate PRDs, plan sprints, triage issues, and materialize tasks into GitHub issues using GitHub-native storage.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project management platform with task checkout, multi-agent coordination, PRD-to-issue pipelines, sprint planning, triage, and GitHub-native storage.

Enables AI coding agents and teams to turn GitHub Projects v2 into an autonomous task substrate for registering, claiming, tracking, reviewing, and completing work, while also supporting AI-powered PRD generation, sprint planning, issue triage, roadmap creation, GitHub Actions/releases/branches, and MCP resources/prompts.

Turns GitHub Projects v2 into an agentic task substrate where AI coding agents register, atomically claim and hand off tasks, heartbeat, submit work for review, and stay within token budgets. Also provides AI-powered PRD generation, task breakdown into issues and milestones, sprint planning, and issue triage — with all state stored natively in GitHub.

Turns GitHub Projects v2 into an agentic project-management substrate where AI coding agents register, atomically claim tasks, send heartbeats, review each other's work, and stay within token budgets, while also offering AI-powered PRD generation, task breakdown, sprint planning, and triage. Everything is stored in GitHub issues, project fields, and comments, so no external database or infrastructure is required.

Turns GitHub Projects v2 into an agentic task substrate where AI coding agents register, atomically claim and complete tasks, exchange heartbeats, review one another's work products, and operate within token budgets. Humans get AI-powered PRD generation, task breakdown, sprint planning, roadmap creation, and issue triage, with all state stored natively in GitHub issues, projects, and comments so no external infrastructure is needed.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables MCP clients such as Claude Desktop to hand tasks to a running DeepSeek Harness window, where each task becomes a real session visible in the sidebar with a reusable session id. If the in-process plugin is unavailable, it falls back to running the task headless so the tool still returns a result.

Enables AI coding agents and human project managers to turn GitHub Projects v2 into an autonomous management layer for task checkout, agent coordination, review workflows, token budgets, AI PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines. All state is stored in GitHub issues, project fields, and comments, requiring no external infrastructure.

Turns any OpenAPI/Swagger specification into a functional MCP server, dynamically exposing API endpoints as LLM tools or generating standalone Python code.

Enables AI coding agents and human managers to turn GitHub Projects v2 into an autonomous project-management layer with task checkout, multi-agent coordination, PRD-to-issues pipelines, sprint planning, triage, token budgets, and GitHub Actions/Releases/Branches through MCP tools, resources, and prompts.

Enables AI coding agents and human managers to turn GitHub Projects v2 into an autonomous task backbone, coordinating multi-agent work, generating PRDs, planning sprints, triaging issues, and shipping code through GitHub-native storage and 20 tools exposing 169 actions.

A Model Context Protocol server that enables LLM agents to manage GitHub repositories, issues, pull requests, branches, files, and releases through a standardized interface.

Enables AI coding agents to register, self-assign and coordinate tasks, track progress, review work, and manage GitHub Projects v2 with AI-powered PRD generation, sprint planning, issue triage, and PRD-to-issues pipelines backed entirely by GitHub-native storage.

An authless Cloudflare Workers server that provides tools to scrape, analyze, and answer questions about websites using Cloudflare's Browser Rendering and AI capabilities.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.