"Accessing Jira Tickets and Updating Their State" matching MCP servers:

A small MCP server that stores and retrieves compact decision-relevant state (goals, constraints, facts, decisions) outside the chat context, enabling easy retrieval for Claude Code or Codex.

Graph-native bounded working memory for coding agents with typed memories, causal retrieval, current-vs-stale state queries, and compact small-model briefs.

Provides state and log management tools designed for long-lived AI agents that may be interrupted and resumed. It enables tracking agent progress and maintaining an append-only event history to ensure continuity across multiple sessions.

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.

SQLite-backed MCP server for Claude Code session persistence and multi-agent coordination. Provides tools for session management, event logging, decision tracking, file locking, agent registry, and plan tracking.

Enables MCP-compatible agents to arbitrate typed state-action schemas, dispatch routine actions deterministically, and apply pre-escalation filters that reduce unnecessary frontier LLM calls. It supports low-latency, schema-enforced routing with safety guardrails and local-first memory retention.

Enables AI agents to commit stateful workflow checkpoints by calculating state hashes and rollback points through the Model Context Protocol. It provides deterministic, dependency-free checkpoint management for autonomous agent execution.

Enables long-horizon AI agents to replace append-only conversation history with a formal, bounded state tuple, supporting state initialization, step execution with transactional rollback, observation injection, and session inspection.

Enables AI assistants to maintain continuity across sessions by tracking named work lanes, structured handoffs, artifacts, and reusable routines so work can pick up where it left off.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

MCP server for Ultrathink: save and search your knowledge base from Claude Desktop, Claude Code, and any MCP client.

Enables researchers to turn property-history questions into reviewable evidence dossiers by gathering sources, tracing people and places, linking conclusions to supporting or opposing passages, and exporting portable backups.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables local MCP clients to list, read, write, and search notes in an Obsidian vault via an HTTP server running inside Obsidian.

Provides MSP support tools (ticket search, draft response, KB search, update) with a deterministic security guardrail that refuses to draft responses for security tickets based on content scanning, even if mislabeled.

Shared versioned state for multi-agent AI workflows. An MCP server.

Connects AI assistants to Tacit building digital twins to query buildings, equipment, sensors, and zones using natural language. It provides tools for exploring Brick-compliant knowledge graphs, fetching historical sensor data, and accessing site documents.

MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.

An MCP server that reads a team's interviews, tickets, and docs to build a model of the product, exposing tools to ask questions, list contradictions and gaps, and draft documents, with all answers citing their source fragments.

Enables coding agents to share a persistent local memory store across sessions and clients, saving, searching, updating, and retrieving facts, decisions, incidents, preferences, references, and snippets with semantic and lexical search.

Enables MCP hosts to access and manage a Lipi vault, including creating, reading, updating, renaming, deleting, and searching notes with romanized Devanagari search.

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 headless MCP server for interacting with Obsidian vaults, enabling AI assistants to search, read, edit, and manage notes and their structure without a GUI.

Stops AI agents reopening rejected decisions and forgetting project state. Persistent operational state for agents: decisions, plans, blockers, priorities and patterns that survive across sessions, with enforcement. Not conversation logs.

Manages local AI skills for Claude Desktop, enabling listing, running, tuning, forking, contributing, and updating skills stored as markdown files. Customizations are persistent and survive updates.

Enables Claude agents to checkpoint their context state and reset back to saved points with handoff messages, maintaining clean context windows during complex tasks by avoiding fragmented summaries from compactions.

Enables reading and updating relationship data (likes, dislikes, important info, feelings, closeness, notes) for characters in a multi-character system, supporting both private and public relations.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.