"Web scraping tools and techniques for data extraction" matching MCP servers:

Enables coding agents to read and modify GitHub issues, project boards, pull requests, repositories, releases, and Actions through configurable toolsets, with read-only and write-confirmation controls.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.

Provides AI assistants with a standardized interface to interact with the Todo for AI task management system. It enables users to retrieve project tasks, create new entries, and submit completion feedback through natural language.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

Enables AI assistants to create and manage visual automation configurations, workflows, and UI states through the Qontinui API. It supports project management, workflow execution, and configuration handling for automated web interactions.

A modular multi-server architecture providing development automation, JIRA management, and performance reporting for Claude Code. It features specialized tools for PR health analysis, code reviews, and generating comprehensive team and individual quarterly reports.

Provides task and project management tools for AI agents, including todo list management, prioritization frameworks like Eisenhower Matrix and RICE scoring, time estimation using PERT, daily standup generation, and sprint burndown calculation.

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.

A production-ready MCP server that connects AI assistants to the D-Tools System Integrator platform, enabling natural language management of AV projects, clients, catalogs, tasks, service orders, and purchase orders.

A Model Context Protocol server providing AI assistants with comprehensive project, task, and subtask management capabilities with project-specific storage.

Provides a read-only MCP interface to Kaiten, letting an agent retrieve cards, spaces, boards, columns, lanes, discussions, checklists, tags, custom properties, sprints and time-tracking reports with paging, filtering and long-text continuation. It also lists card and comment attachments and downloads selected originals as local files, with hashes and safe unique names, for further agent analysis.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Enables Codex projects to read Git-backed kickoff, acceptance, handoff, progress, and next-step context, and to append validated, audited progress events through scoped MCP tools. This supports visible agent progress, resumable sessions, and safer handoffs.

Enables Codex and other MCP clients to read kickoff cards, acceptance criteria, Git evidence, and next steps, then append validated, audited progress events for resumable project handoffs.

Enables AI-powered project management by connecting Claude to Planka kanban boards via 75+ MCP tools for creating, updating, and managing projects, boards, lists, and cards.

Centralized MCP server for spec-driven AI agent workflows, enabling isolated feature management, task tracking, and implementation with handoff and archiving capabilities across multiple projects and developers.

Enables agents to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited progress events with matching Git commits through short-lived scoped credentials.

Enables AI agents to retrieve Git-backed project context, handoff packages, progress, and next steps, and to append validated progress events with matching project-record commits. This supports visible agent progress, resumable work, and safe handoffs while keeping high-risk actions outside the MCP surface.

Enables agents to read Git-backed project context and append audited, idempotent progress events through scoped, short-lived credentials, supporting resumable handoffs and visible project state.

Enables AI agents and users to verify claims about Jira issues and issue counts against live Jira, retrieve verifiable facts for drafting updates, and re-check previously posted claims. It provides read-only tools and an issue panel so status updates can be evidence-based and mismatches corrected before or after posting.

Enables Codex sessions to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail, and next step, then append validated, idempotent progress events backed by matching project-record Git commits. Access is limited to a short-lived, revocable credential scoped to one workspace and project, with high-risk actions kept outside the server.

Enables AI agents to read Git-backed project context and append validated, audited, idempotent progress events through short-lived, scoped credentials, supporting resumable work and safer handoffs.

Enables AI assistants to deeply introspect Jira Data Center configurations — including workflows, schemes, automation, and Assets — through 76 read-only tools, without any modification capability.

A Model Context Protocol (MCP) server that connects AI assistants to Jira Server/Data Center, enabling issue management, JQL search, sprint tracking, and natural language interaction with Jira.

Enables Codex agents to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail and next step, then append validated, audited, idempotent progress events that become matching project-record Git commits. Access is scoped to one workspace and project through short-lived, revocable, hash-stored credentials that cannot touch members, keys, deletion, publication or deployment.

It enables AI agents to retrieve Git-backed project context, handoff packages, and next actions, then append validated, audited progress events as project-record commits.

It lets AI coding clients read a project’s kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append a validated, audited, idempotent progress event with a matching project-record Git commit.

Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events with a matching Git commit.

A Model Context Protocol server that provides AI assistants with structured access to your Logseq knowledge graph, enabling retrieval, searching, analysis, and creation of content within your personal knowledge base.

Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events backed by a matching project-record Git commit. Access is scoped to one workspace and project via short-lived, revocable, hash-stored credentials that cannot reach members, keys, deletion, publication, or deployment.