"Sailfish OS" matching MCP servers:

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Enables corpus-grounded research over Lacanian seminar and écrits texts by retrieving passages, building evidence contracts, and returning only answers whose claims survive citation and entailment validation — abstaining instead of answering from model knowledge. It also exposes the corpus for direct reading and lets users audit every claim back through answer → claim → passage → session → seminar → witness/source.

Enables source-first orchestration and knowledge indexing with inspectable architectural capabilities through a unified MCP interface, including named-attribute retrieval and atomic knowledge ingestion.

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

OpenCrab provides an MCP interface for the MetaOntology OS, enabling structured knowledge management across graph, vector, and document databases. It allows agents to perform hybrid searches, manage complex entity relationships, and conduct impact analysis within a multi-space ontological framework.

Serves an AI coding agent a searchable index of a codebase's existing capabilities and past incidents, so it can find and reuse what already exists before writing new code. Also exposes blast-radius analysis for shared code and lets the agent reindex the knowledge base, all via local retrieval with no model calls or API keys.

Drop-in memory layer for AI coding agents, upgrading them from chat history to a governed Memory OS with hybrid search, contradiction detection, and safe governance.

MCP server for Agent Context OS that compiles engineering docs into a knowledge graph, detects code drift, and serves token-budgeted context packs to AI coding agents via MCP.

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

Persistent long-term memory for AI coding assistants. Local SQLite, no cloud - 16 MCP tools to store, search, relate, and consolidate typed memories with a confidence lifecycle, hybrid BM25 + semantic search, namespaces, a knowledge graph, and a built-in OS keychain credential vault.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

An MCP server that enables web search and page content retrieval via the Keenable API, supporting search with filters and fetching clean markdown content from indexed URLs.

Enables coding agents to query a team knowledge base via MCP, performing semantic search and asking questions that return grounded, citation-backed answers from ingested documents.

Enables LLM hosts to perform grounded, cited retrieval and answer generation over your own documents using hybrid BM25 and dense search, with explicit refusal when answers are not supported by the sources.

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

Enables AI assistants to search the web, conduct deep research, extract web content, and get AI-powered answers in real-time via the KEIRO API.

A server implementing Model Context Protocol that enables AI assistants to interact with Slack API through a standardized interface, providing tools for messaging, channel management, user information retrieval, and more.

Persistent, consensus-validated institutional memory for AI agents. Gives LLMs real memory that survives across sessions - validated through BFT consensus, not just dumped to a file.