"MCP server with task management system for coding projects" matching MCP servers:

Enables managing GitHub Projects v2 boards through Claude Code and Codex, including project and item administration, field updates, sprint boards, epic rollups, and desired-state planning.

Enables AI assistants to manage GitHub Projects V2, including items, fields, and views through a standardized interface.

github-projects-mcp

Enables users to interact with GitHub's Projects v2 API through natural language for Agile project management, supporting repository details, issue tracking, and project board management operations.

Gives any MCP-compatible AI chat or agent a safe, model-neutral coding runtime with file read/search, structured multi-file patches, command execution, interactive sessions, and git operations, all confined to a single workspace and gated by permission modes.

Enables AI agents to read GitHub Projects v2 boards over stdio, letting them list projects and their items across repositories so cross-repository work can be coordinated without scanning every repository. The read-only MVP authenticates via a GitHub App installation token minted at runtime and exposes list_projects, get_project, and list_project_items tools with cursor-based pagination.

A production-oriented MCP server for coding agents that enables multi-project management through secure file operations, Git integration, and safe command execution. It supports project discovery across multiple root directories and provides robust audit logging with both STDIO and HTTP transport options.

Provides an MCP server for scraping and retrieving data from GitHub Projects, including issues, pull requests, and organizational metadata. It enables natural language interaction with project boards and repository contents using GitHub Personal Access Tokens.

An MCP execution layer that lets capable AI models safely control a developer workstation for file edits, terminal and process execution, Git operations, language-server analysis, browser and Windows UI automation, media processing, job/resource control, and checkpointing. It also coordinates durable single- or multi-agent tasks across providers with leases, dependency graphs, evidence logs, repair loops, and separate verification gates.

Enables AI clients such as ChatGPT and Claude to safely read, analyze, update, verify, and audit GitHub Projects v2 through OAuth-secured MCP connections with role-based access control, guarded writes, bulk preview/approval/apply, checkpoints/deltas, and durable audit trails.

Enables managing GitHub Project views, priorities, dependencies, and metrics through natural language.

Gives MCP-compatible AI clients safe, hands-on access to local codebases: file reading/search, multi-file patches, command execution, interactive sessions, Git inspection, and coordination of local agent providers such as Antigravity and OpenCode.

Enables MCP-compatible AI clients and coding agents to turn vague GitHub requests into structured, testable task contracts, inspect repository evidence, simulate execution, validate readiness, and preview or publish Gibwork bounties only after explicit confirmation.

A local MCP server that gives AI coding assistants read, write, search, and execute capabilities within a specified project directory. This Windows GUI build simplifies setup by eliminating manual Python, Node.js, or Docker installation.

Fetches, summarizes, and reviews GitHub code diffs with asynchronous processing for large diffs.

Turns local project directories into persistent MCP workspaces, allowing AI agents to read files, modify code, run commands, manage Git, and save session progress across conversations.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

Enables Claude to independently check an AI agent's work in a local git repository by recording a baseline, running only the checks relevant to the changed files, and cross-checking what the agent claimed. Returns a compact, evidence-labelled report with a verdict and a ready-to-paste next prompt, so unverified success claims can't slip through.

Enables task management and automated development workflow tracking with Eureka Labo, including creating/updating tasks, starting work sessions, and automatically capturing git changes with diff logging.

Enables AI agents to automate project management on self-hosted Forgejo v15, including managing Projects/Kanban boards, columns, cards, issues, and milestones, despite Forgejo lacking a REST API for Projects.