"A guide to backtesting strategies and tools" 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.

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.

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 agentic co-authoring of feature specs, decomposition into architecture-validated tickets, and idempotent syncing to Linear as projects with epics, sub-issues, and dependencies.

Lets AI agents turn a repository's git history into proposed GitHub issues grouped into units of work, each with a commit checklist and links, then create and close them only after approval. Planning is read-only and creation defaults to a dry run, skipping anything that already exists.

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.

Enables AI clients like Claude to read and manage Microsoft To Do task lists and tasks via the Microsoft Graph API, running locally over stdio with secure token storage.

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.

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.

Enables managing Microsoft To Do lists and tasks through MCP, including creating, updating, completing, deleting, searching, and checklist operations via Microsoft Graph.

Enables to manage to-do items through natural language, with tools for creating, reading, updating, and deleting tasks.

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.

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 AI to read live weather data and manage a persistent to-do list through MCP tools, demonstrating both read and write capabilities without API keys.

Lets Claude and other AI clients read and modify Microsoft To Do through natural language, adding, completing, searching, updating, and deleting tasks and sub-steps by title and list name instead of ids. Personal Microsoft accounts need no Azure app registration — a single device-code sign-in grants access, with optional read-only and no-delete modes available.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

MCP server for Redmine that enables interaction with issues, wiki pages, and time entries through natural language.

Enables coding agents to manage Microsoft To Do lists and tasks through Microsoft Graph, with optional support for checklist items, linked resources, attachments, and delta synchronization.

A Model Context Protocol server that helps collect and structure project portfolio information through a guided conversation flow.

A Model Context Protocol (MCP) server that enables AI assistants like Claude and Cursor to interact with Microsoft To Do via the Microsoft Graph API.

A Model Context Protocol (MCP) server that enables interaction with JIRA APIs through Claude Desktop, allowing users to search, create, update, and manage JIRA issues using natural language commands.

A comprehensive MCP server providing advanced Redmine project analytics, web automation via Playwright, and iTunes music integration. It enables detailed tracking of sprint metrics, bug counts, and team performance through a token-optimized tool architecture.

Enables an AI assistant to manage a simple to-do list stored in a local JSON file, with tools to add, list, get, complete, and delete tasks, plus a read-only pending tasks resource.

Enables AI-assisted field service management through the Service Fusion API, including job lookup, customer management, dispatch, invoicing, and equipment tracking.

Connects Claude to Jobber to manage clients, jobs, invoices, quotes, and scheduling through natural language.

Enables AI agents to read and edit Microsoft To Do tasks, lists, and steps via Microsoft Graph, including due dates, reminders, and subtasks.