"A system for task management in coding projects" matching MCP servers:

Enables clients to retrieve structured work briefings and item details, analyze blockers, and submit next-action proposals through streamable HTTP tools backed by Amazon Bedrock conversations. Supports human-confirmed approval or cancellation while preserving revisions, decision histories, and safe reuse or invalidation of pending proposals.

Enables AI agents to manage live Firefox tabs and native tab groups via MCP tools over stdio, with exact-match verification and safety constraints. It does not read page content or send browser data remotely.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Proxies a remote MCP server to add protocol-native background task support, including task management and progress forwarding, while preserving synchronous calls.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

Async MCP server for running long-running AI tasks with real-time progress monitoring, enabling users to start, monitor, and manage complex AI workflows across multiple models.

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.

Enables supervising and orchestrating local coding agents like Muse and AGY through a client-agnostic MCP interface, with isolated Git worktrees, safe execution, and deterministic verification.

An MCP server for task orchestration.

This MCP server enables agents to manage complex tasks by providing tools for registration, complexity assessment, breakdown into subtasks, and status tracking throughout the task lifecycle.

Enables agents to select the provably optimal set of candidate actions under a budget, with optional conflicts and prerequisites, and to re-plan to the single best next action after each outcome. Also validates any proposed selection for feasibility.

Enables Codex to manage a local Claude Code companion through MCP, implementing a dual-agent workflow where Codex handles reasoning and review while Claude Code performs engineering tasks.

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.

Enables MCP clients to batch repetitive web admin work by harvesting queue items read-only, collecting verdicts, and applying them only after human approval, with dry runs, staged rollout, rate limits, a circuit breaker and an audit log. Also provides general browser control — navigating, reading, filling forms and clicking on allowed sites through an already logged-in local browser, pausing for confirmation before irreversible actions.

Enables Claude Code to control Firefox through tools for tabs, navigation, clicks, typing, scrolling, screenshots, page reading, forms, JavaScript, and console/network logs.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Provides structured workflows (phases, gates, coordination) for AI agents, enabling complex task execution with quality enforcement and multi-agent coordination via Model Context Protocol.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables AI coding agents from different MCP-capable clients to exchange messages in real time through a shared in-memory broker. Supports agent registration, inboxes, and live event streaming without requiring a database.

Enables creation and management of scheduled tasks with interval, cron, or one-time triggers. Persists tasks in SQLite and supports MCP sampling to automatically invoke AI agents when schedules trigger.