"Building a solid memory base for AI development" matching MCP servers:

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.

Enables AI clients to access a shared, authenticated memory and project management system with durable storage, task tracking, roadmaps, and semantic search, deployed on Cloudflare.

MCP server for IDEA Base — AI-powered project management. Manage projects, tasks, and time tracking directly from Claude Code, Cursor, or any MCP-compatible AI tool.

Project Memory stores decisions, evidence, outcomes and reviewed lessons in local SQLite. Assistants retrieve bounded context through three MCP tools. People follow and plan work in a live workspace with an overview, sprint board, decision history, readable documents, skills and project maps. Offline exports remain available.

Persistent, branch-aware workflow state memory MCP server for AI coding assistants. Tracks tasks, accepted decisions, and active blockers to prevent session context bloat and speed up development.

Enables MCP-compatible clients to manage AI agent teams, including agents, Kanban issues, projects, goals, approvals, budgets, and raw API access.

Bridges disconnected AI sessions with persistent project memory and automatic session handoff, integrating GitHub workflows for context-aware development.

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

Enables households to maintain a shared, persistent family memory for tracking item locations, warranty dates, chores, and who said what and when. It exposes this memory to AI assistants and tooling through MCP-compatible endpoints.

A project state control plane for multiple AI agent sessions to share structured conclusions such as tasks, checkpoints, code maps, decisions, and handoffs. It enables agents to read and write persistent project state via MCP tools while humans track progress through a lightweight panel.

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.

Provides memory and project tracking for Claude Code via MCP, enabling semantic search over past transcripts, durable notes, and structured project management with milestones, epics, tickets, and todos.

A deterministic MCP server that reimplements ai-git-fish workflows (aicommit, aibranch, aipr) with Leantime integration, enabling Claude Code and Codex to perform git operations and manage tickets without an internal LLM.

Enables teams to measure their actual ticket-writing style from GitLab, Jira, or GitHub and check new or draft tickets against that learned house profile, with optional model-backed drafting.

Provides AI-driven project memory management through structured prompts that help Claude parse tasks from specs, review code changes, sync with commit history, and maintain project documentation without directly accessing files.

A shared coordination layer for multiple AI coding assistants, exposing a persistent task queue, per-task message threads, and progress tracking via JSON files on disk.

Enables multiple AI agents and humans working in the same project to share status, exchange messages, and claim files through a local collaboration board. It supports project-specific enablement, conflict-aware file claims, and shared state via SQLite.

An AI-native Taskwarrior bridge that provides natural language task management for Claude Code and other AI systems, integrating with existing Taskwarrior infrastructure.

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

A Model Context Protocol server that provides structured workflow tools for managing software development projects through different complexity levels, offering specialized modes for project planning, design, implementation, and documentation.

Enables autonomous AI-to-AI collaboration between Claude and Gemini to execute complex development projects with minimal human intervention. It provides a role-based system with task dependencies, automated project planning, and continuous execution loops.

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.

An MCP server that helps teams create, manage, and access structured project documentation through six core document types, leveraging AI to generate comprehensive project knowledge management.

Enables deterministic GitHub issue and pull request delivery workflows, including issue creation, development, verification, PR publication, review, and merge, with strict configuration and admission controls.

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 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 agents to store, search, and manage persistent memories, todos, kanban boards, reminders, and progress trackers in a local SQLite database.

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.

MCP server that enables AI agents to access and modify Todoist tasks, such as finding tasks by date and adding tasks, via natural language.

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 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 to file and track issues, plan epics with steps, comment as they work, and hand decisions back to the user through a local Markdown- and YAML-backed issue tracker.

Enables Codex agents to read a project's kickoff card, acceptance criteria, handoff package, progress, Git trail and next step, then append validated, audited, idempotent progress events that become matching project-record Git commits. Access is scoped to one workspace and project through short-lived, revocable, hash-stored credentials that cannot touch members, keys, deletion, publication or deployment.

It enables AI agents to retrieve Git-backed project context, handoff packages, and next actions, then append validated, audited progress events as project-record commits.

It lets AI coding clients read a project’s kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append a validated, audited, idempotent progress event with a matching project-record Git commit.

Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events with a matching Git commit.

An MCP server for intelligent memory and task management with semantic search, automatic task extraction, and knowledge graphs, enabling AI assistants to maintain context and learn project conventions.