"Agent File Control MCP Server" matching MCP servers:

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 agents to securely read, plan, and sync real trips from the Trek WeChat mini-program via authenticated remote MCP, supporting tools for itinerary management, reservations, and file attachments.

YOUR AGENTS COLLIDE. File a FlightPlan. Run multiple coding agents without them stepping on each other. FlightPlan gives each agent the same preflight picture, lets them coordinate while plans are still cheap to change, and leaves behind what changed and why for whichever agent comes next. Across sessions. Across people. Across providers. Across time. One shared picture.

Enables AI agents to interact with issue, comment, document, and agent workflows through a simplified HTTP API, returning compact Markdown or file-based snapshots.

A dual-mode MCP server for integrating Feishu/Lark project management, enabling task CRUD, advanced filtering, and seamless integration with AI assistants and automation workflows.

A production-ready MCP server for triaging and reviewing GitHub pull requests via the GitHub REST API, providing typed tools to list, inspect, comment, add labels, and submit reviews.

Enables Claude to interact with Jira, Salesforce, and n8n through MCP tools, allowing automated reading of Jira stories, deploying Salesforce metadata, and triggering n8n workflows.

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.

Enables Claude Code to control a Planka 2.x board via 15 MCP tools, with writes re-read and verified so reported success matches the board, plus an optional workflow that turns the board into durable agent memory.

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

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.

Provides tools for managing tasks, searching docs, and running a heuristic quality gate to check agent output for common issues before human review.

An MCP server that connects AI assistants to Notion, enabling automated research, GitHub tracking, and content pipelines with human-in-the-loop approval via a Notion task queue.

A Model Context Protocol server for AI agents to manage tasks and track progress across projects, with features like project isolation, search, and reporting.

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.

Experimental MCP server for coordinating CLI agents across projects using file-based task boards and assignment tracking.

Forgespec MCP facilitates Spec-Driven Development (SDD) by providing tools for contract validation, task board management, and advisory file locking. It enables multi-agent AI systems to coordinate complex workflows through a structured nine-phase development pipeline with built-in dependency tracking.

Enables AI agents to create and manage small project plans—including tasks, assignees, status, progress, dates, and dependencies—and retrieve Gantt-friendly project views over MCP stdio. State is stored in SQLite without external dependencies.

Enables AI agents to manage Dida365 tasks via natural language with a rule engine for automatic project routing, priority assignment, and label management.

A control plane for AI agents and human supervisors. Persistent task registry with scoped permissions, inter-agent delegation, and full provenance — all accessible via MCP. Deploy on Supabase free tier in 3 commands.

A tasks and projects board MCP server for agents, providing create, list, and status update tools with agent-scoped access via control-plane proxy.

A secure, TypeScript-based MCP gateway that enables AI agents to interact with Jira through controlled, audited tool calls without exposing credentials.

Lets agent lanes and their supervising human share one protocol-governed, local-first queue where requests, questions, handoffs, approvals, and verifications are logged as typed items with immutable history and evidence refs to commits, tags, runs, and artifacts. Exposes this over stdio or Streamable HTTP so MCP clients can file, acknowledge, transition, and verify work while the daemon and SQLite event log stay on the user's machine.

Provides tools for coordinating AI agent work on one machine through a local SQLite-backed queue and kanban, including task creation, atomic claiming, lease renewal, completion/failure, listing, comments, and cancellation.

File-based MCP server for AI coding agents to coordinate via inbox messaging and human escalation.

AI agent can manage Redmine tickets and projects via MCP tools.

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.

Enables software agents to self-register, publish and read structured notes, questions, tasks, and results in public namespaces, and coordinate work via versioned task claims, replies, and incremental change synchronization over MCP.

Enables agentic CLIs to start, manage, and resolve structured mediations between product managers and architects, following a protocol to separate positions from interests and produce auditable recommendations.

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.