"Replicating ChatGPT Memory Functionality for Task Management and Skill Tracking" matching MCP servers:

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.

Provides access to OpenAI's ChatGPT API with web search capabilities for Claude and other MCP clients. Supports various GPT models with configurable parameters like reasoning effort, temperature, and streaming mode.

A self-hostable semantic skill registry for AI agents, providing searchable, versioned, and verified skills over a single MCP endpoint with per-agent private vaults and trust tiers.

About Your task manager is the best agent memory you're not using. An agent-native context layer over your existing task app.

Enables agents to maintain multi-tier memory across working scratchpad, dialogue buffer, and episodic stores with recency decay. Supports hybrid BM25/vector retrieval, rank fusion, graph expansion, and context reordering for optimized MCP-based memory and RAG workflows.

Provides Claude Co-work with MCP tools to search and record organizational memory, including search, read, query, ingest, remember, sync, and status operations.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.

Enables MCP-compatible agents and IDEs to retrieve episodic long-term memories using hybrid BM25 keyword search, semantic n-gram cosine similarity, and recency decay ranking, with deterministic zero-dependency execution.

Enables a coding agent to point a task prompt at the single right entry in a library of SKILL.md files, ranking names and descriptions with BM25 and returning the winning skill's full body plus any companion skills to load, or nothing at all when no skill confidently applies.

MCP server that connects Claude Code to Substrate organizational memory, providing tools for searching, reading, querying, and writing memory, with automatic capture of conversation turns.

Improves AI agent task performance by providing task area segmentation, hierarchical RAG, and hybrid search capabilities.

Enables AI agents and MCP-compatible clients to perform hybrid episodic long-term memory retrieval by combining BM25 keyword search, semantic n-gram cosine similarity, and recency decay ranking over stored memories.

MCP ChatGPT Responses connects Claude to ChatGPT through two essential tools: standard queries for AI-to-AI conversations and web-enabled requests for current information. It uses OpenAI's Responses API to maintain conversation state automatically.

Exposes task management (add, list, complete tasks) and document search (RAG) as MCP tools for AI agents.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Embedded, local-first agent memory: facts extracted into a per-namespace SQLite file (vec0 + FTS5) with hybrid retrieval and point-in-time (time-travel) queries. ADD-only history over stdio — no server process, no cloud dependency.

MCP server providing persistent memory for AI applications, enabling Claude to store and recall memories with hybrid search and knowledge graph.

Exposes tools that let an agent search a local Markdown-based memory store, fetch full cards by id, write new knowledge cards that are indexed immediately, and inspect or rebuild the SQLite index. All retrieval runs locally over Chinese-friendly full-text search with graded exact/prefix matching, so agents without a memory system can recall prior notes while existing Markdown files stay read-only.