"Threads" matching MCP servers:

Enables MCP-compatible coding harnesses to read Amp threads as Markdown, with pagination and filtering options, through a read-only interface.

Persistent knowledge layer for AI agents. Structured KB with search, investigation threads, multi-session journal, and multi-agent attribution. SQLite or PostgreSQL.

Self-hosted server that generates and serves Universal Context Packages (UCP) to AI agents via MCP, turning complex issue threads into structured, verifiable context.

Enables semantic search and retrieval of archived AI conversations from multiple providers via the MCP protocol, allowing thread continuation and integration with MCP-capable tools.

DM / IM for AI agents over the A2A 1.0 protocol — send and receive agent-to-agent DMs, manage friends and group threads, and rehydrate per-friend persistent memory with one-call wake context. 12 tools, pip install agoradm-mcp, stdio transport.

MCP server for structured reflection and self-modeling over Everlog diary exports, enabling agents to query local diary evidence and maintain versioned artifacts of threads, moments, beliefs, and decisions.

Local-first WhatsApp and iMessage memory for AI coding agents. It provides MCP tools to search messages, get recent context, summarize relationships, draft replies, and view unreplied threads.

A Model Context Protocol server that provides persistent memory and conversation continuity for Claude Desktop and Claude Code, allowing users to save and restore project context when threads hit token limits.

Enables persisting chat-thread notes to SQLite with upsert semantics, allowing creation, update, retrieval, and listing of per-user threads via MCP tools.

Local-first dev memory: indexes Git commits, PRs, Jira/Linear tickets, Confluence docs, Slack threads, and Calendar events into a local SQLite/FTS5/ONNX index, and exposes them as MCP tools so Claude Code, Cursor, and Codex can search and cite your past work.

Structures AI conversations into hierarchical thread trees, replacing full history with concise summaries to reduce token consumption and preserve context.

Multi-agent shared brain MCP server enabling cross-session memory, self-improving skill loops, and inter-agent signaling across Claude, Codex, Gemini, Copilot, and VS Code CLI agents.