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

A Model Context Protocol server that converts Markdown content to HTML format.

Enables an Alexa+ host to place and manage customer-care calls by building a case, navigating phone menus, waiting on hold, explaining the issue, guarding sensitive disclosures, handing off identity checks, recording ticket numbers and promises, and scheduling follow-ups.

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.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Plan SEO pages in an SEO Content Machine Workspace, then have its page agents research, write and review each page as a draft. A stdio bridge to the SCM desktop app, which must be running on the same machine.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

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

Exposes GitHub issue and pull-request triage capabilities to any MCP client: fetching repository context, classifying and prioritizing requests, finding duplicates, and applying labels, comments, assignments, closures, or reopenings. All writes are policy-gated, dry-run by default, and destructive actions require explicit two-step human confirmation.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables AI agents and project managers to turn GitHub Projects v2 into an autonomous project-management layer, handling task checkout, atomic claims, heartbeats, reviews, token budgets, and AI-powered PRD, sprint, triage, and roadmap workflows. It also provides GitHub Actions, Releases, Branches, MCP Resources, and MCP Prompts support with GitHub-native storage.

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.

Enables AI coding agents to register, atomically claim tasks, heartbeat, and review each other's work while turning GitHub Projects v2 into an autonomous task backbone. Also provides AI-powered PRD generation, sprint planning, issue triage, and a PRD-to-issues pipeline backed entirely by GitHub-native storage.

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.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

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.

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.

MCP server for qualifying and responding to inbound leads in seconds using a multi-agent AI pipeline.

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.

Turns GitHub Projects v2 into an agentic task backbone where AI coding agents register, atomically claim and track work, heartbeat, review each other, and stay within token budgets, while humans get AI-assisted PRD generation, sprint planning, triage, and PRD-to-issue pipelines. All state is stored natively in GitHub issues, project fields, and comments, so no external infrastructure is required.

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.

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.