"Information on Working as an Actuary" matching MCP servers:

Provides local persistent working memory for AI agents, allowing them to load rules, preferences, and project state before tasks and save validated experiences after successful completion. Works with stdio MCP clients via a local JSON file.

Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.

Prevents context bloat and the 'Lost in the Middle' phenomenon by distilling action histories into concise summaries while maintaining a clear core objective.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

Enables insurance claims review assistance by querying a knowledge graph of Korean standard insurance terms, restoring applicable policy versions by enrollment date, and returning coverage/exclusion determinations with cited provisions.

Enables searching imported AI conversations locally across different providers from an MCP client, with read-only access to the archive.

Enables AI assistants to build and query temporally-aware knowledge graphs from conversations and data. Supports adding episodes, searching entities and facts, and maintaining persistent memory across interactions.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

Enables a simulated Alexa+ care companion to capture daily check-ins, recall longitudinal care-journal history, assess risk, create local family-inbox cards, schedule follow-ups, and produce weekly digests through MCP tools.

Refines development prompts and stores semantic memory to save tokens in complex Antigravity tasks, enabling token savings and enriched context.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Lets AI assistants understand what you're working on — current screen content, recent dictation, clipboard, and saved notes — running entirely on your own machine with nothing sent to the cloud.

Long-term memory for Claude Desktop and Claude Code over plain markdown files on your machine. It returns nothing when the corpus has no answer, naming the terms that appear nowhere — no least-bad match dressed as an answer. And it verifies cited commit SHAs against git, so an agent can tell what actually shipped from what was only discussed and abandoned. Local; nothing is transmitted.

Rabbithole provides an infinite canvas for learning by allowing users to open documents, select text, ask questions, and receive answers that open as child documents, all running locally via an MCP server.

A plain-files brain template and MCP server that lets models read owned, portable working memory via list, read, and grep-style search tools.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

An MCP server that provides on-demand skill discovery for AI coding agents by querying GitHub repositories, using BM25 search to return relevant SKILL.md content.

Provides an AI agent with a searchable markdown notes vault, offering tools to create, read, list, search, update, and delete notes stored as plain .md files.

An MCP server that gives AI agents persistent, narrative memory: concepts as nodes, relationships as typed "because" edges, so anything filed can be pulled back by association rather than by address.

MCP server for FOLIO, the Federated Open Legal Information Ontology. Makes the full ontology available to AI agents as searchable, browsable tools.

Enables MCP-compatible AI agents to connect to SoluCortex projects, recall relevant technical decisions, conventions, risks, and architecture before working, and record new memories afterward.

AutoMem MCP provides persistent memory for AI assistants, enabling them to recall information across conversations and platforms with graph-vector retrieval.

An MCP server that stores notes as Markdown files on your machine, enabling you to save, search, and manage notes through natural language with Claude Code or Claude Desktop.

Exposes a materialized service dependency graph as an MCP toolset for persistent, queryable root-cause analysis via Cypher queries.

An MCP server that gives agents persistent memory with namespaced facts, tags, full-text search, and TTL expiry, all running locally on SQLite with zero external dependencies.

An MCP server that lets Claude Code recall the context of past conversations from any project on demand.

An MCP server that provides persistent memory capabilities for AI agents using Mem0, enabling storage, search, and management of contextual information across conversations with support for multiple backends and LLM providers.

An MCP memory server for coding agents that checks stored facts against the filesystem and git before relying on them, flagging stale memories.

Public, agent-searchable knowledge base about AI-native software development, served as an MCP server with tools to search, read, and list topics.