"General search for the term 'Agent'" matching MCP servers:

Enables MCP-compatible assistants to connect to a user's workspace, read across boards, notes, checklists, habits, money, meals, chores, and chat, and make scoped additions, changes, or removals with attribution.

An MCP server that provides shared memory, kanban board, and agent registry for AI agents to collaborate as a team, with a live dashboard for human oversight.

Enables people to open a shared group chat as a card inside their own AI chat, where they and their AIs talk together and post, claim, and confirm tasks on a self-organizing board. Its tools also let any AI read the repository's code and submit a proposed change that becomes a pull request.

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 for Agent Room, enabling AI agents to join shared meeting rooms and collaborate with humans via tools like room_listen and room_task_*.

Enables AI coding agents to coordinate through a local, pull-only message board by registering sessions, posting updates, proposing and accepting tasks, holding leases, and reading or acknowledging updates under scoped human authorization.

MCP server that connects AI assistants to Instructure Canvas LMS, enabling teachers and administrators to manage courses, assignments, grades, and more through natural language.

Enables search and management of Azure DevOps work items and wiki pages via MCP, wrapping the ado-search CLI.

MCP server that enables AI agents to manage Dida365/TickTick tasks, projects, tags, and habits through natural language, with full CRUD, search, and advanced V2 capabilities.

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 AI agents to coordinate open projects by registering, creating and claiming tasks, submitting and reviewing work, electing coordinators, and chatting in a shared lobby.

Attaches a file-based kanban workflow to any project, allowing agents to create, claim, complete, and block work items using git as the locking mechanism.

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 AI agents to maintain project continuity through a file-based state hub with tasks, phases, and handoff snapshots. Provides MCP tools for reading and updating project state, with gatekeeping enforced via real-state evaluation and per-tool authorization.

Enables people and their AI agents to share a kanban board whose tasks, hand-offs, reviews, notes and alerts live as markdown files in a private GitHub repo, with per-person access control. Works from Claude, ChatGPT, Claude Code, Codex or any MCP-speaking client, and can draw the board inside chats.

An MCP server enabling AI coding agents to interact with a task tracker that enforces rules server-side, replacing markdown files and hooks with a database, CLI, and web UI.

A task orchestration system for AI agent teams that provides a Kanban dashboard and 12 MCP tools to manage multi-step workflows with DAG dependencies. It enables agents to coordinate through task threads, automated retries, and real-time webhook notifications.

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.

Enables an MCP-capable coding agent to run a local-first job search: recording verified opportunities in a private SQLite tracker, tracking follow-ups and outcomes, and preparing evidence-based resumes, application answers, and outreach drafts. It keeps all personal data on the user's machine and stops before submitting applications, uploading documents, or contacting anyone.

Enables pipeline-driven task management for AI coding agents, with stage-gated workflows, dependency tracking, artifact versioning, and multi-agent collaboration.

Enables any MCP-capable agent to maintain a shared .apm Markdown source of truth for project goals, tasks, decisions, handoffs, and health insights. It lets multiple agents and CLI/dashboard tools coordinate using the same file-based read/write logic without a database.

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 coding agents on the same machine to exchange local messages, manage and claim tasks, and coordinate folder locks through stdio MCP tools backed by plain files. It runs without a network server or dependencies and supports concurrent agents.

Enables AI agents to create projects, post rich status updates with images and video, claim tasks, read replies, and gate work behind user approvals over a live browser dashboard.