"Information on Air Quality Index (AQI)" matching MCP servers:

Provides local-first retrieval over long design conversations, enabling users to find where a decision was made, why, and what replaced it, with turn and line range citations through hybrid retrieval, typed judgment rerank, exact search, and five MCP tools.

Audits your Claude Code memory store with 4-dimension quality scoring and actionable cleanup recommendations, including a visual dashboard.

Governed knowledge base for AI agents via the Model Context Protocol (MCP), enabling agents to search, read, and contribute persisted knowledge with versioning, audit trails, and approval workflows.

Enables indexing and retrieving notes with full-text search using SQLite, plus building knowledge graphs to find relationships between concepts. Supports natural language note management, tagging, and semantic connections.

Enables voice captures from a smart ring to search and append notes in a local Obsidian vault and query an OpenAI-compatible AI agent, returning answers as phone notifications.

A lightweight MCP server that maps keywords to file paths instantly using a JSON index, enabling fast context retrieval for AI agents without embeddings or vector databases.

AI memory that works like yours. Neural pathway architecture gives your AI persistent recall, contextual awareness, and cross-session continuity the way human memory actually works. 14 MCP tools. Works with Claude Code, Cursor, Windsurf, and any MCP client. $50/mo unlimited.

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 agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.

An MCP server that stores a household's city and members — including children and asthma — across sessions, pulls live air quality (estimating US AQI from PM2.5 when needed and falling back to cached readings on network failure), and turns it into concrete school-morning, evening, or right-now plans covering outdoor activity, window timing, and masks. It also keeps named routines and a history of past plans, exposing them through tools plus a household profile resource.

docshelf-mcp manages AI-friendly document collections — converts PDFs and Markdown into chapter-split shelves with a single navigation INDEX, so AI agents can fetch only the relevant section by raw URL instead of choking on a 4 MB datasheet. Repo: https://github.com/ignatenkofi/docshelf-mcp

Enables MCP-capable agents to query a LightRAG knowledge graph for grounded answers with source files, ingest documents into the index, and retrieve indexing statistics.

Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.

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

Indexes the session histories Claude Code, Codex CLI and opencode already write into a local searchable memory. MCP recall tools, session-start auto-recall, secret redaction at index time, cross-machine sync over SSH.

Search past OpenCode conversation history before starting new work on a module or file, via a local read-only FTS5 index built from OpenCode's own SQLite database. No network calls, fully local. 7 tools for keyword search, file lookup, and session browsing.

A memory system for AI agents that maintains a human-readable, typed Markdown knowledge base with an always-in-context index, enabling recall, correction, and trust decay through MCP.

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.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Provides read-only MCP tools to inspect imported history sources, list sessions, search literal text, and read paginated event history from a local SQLite index.

An MCP server that provides coding models with a live code index, inferred code graph, durable memory, and surgical tools to help them leverage their existing reasoning and coding abilities effectively.

Enables MCP-capable coding agents to semantically search, store, and inspect a single local, cross-tool index of session histories and project docs. Agents can retrieve what other tools and prior sessions already discovered.

Zero-trust, air-gapped Enterprise GraphRAG MCP server. Build knowledge graphs from local documents and run multi-hop, citation-grounded queries entirely offline with Ollama.

Enables coding agents to store, search, and retrieve long-term memory as plain Markdown files with a disposable SQLite index, including note management, decision/bug tracking, and codebase symbol lookup via MCP.

Enables project-scoped agent memory backed by a per-project SQLite index and raw data store, plus a global registry for discovering local memory workspaces. Agents can search summaries, retrieve original records on demand, save new memories, and link related records without sharing memory across projects.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

A neutral memory quality-gate for AI agents — a gate, not a store. It provides one shared memory of you that every AI agent reads from and writes to, kept honest at write time.

Provides persistent, searchable memory for AI agents, enabling them to retain, recall, and reflect on information across conversations.

A system for defining, composing, and managing task-specific contexts for AI-powered development, enabling consistent, high-quality results.

Local index and hybrid search (SQLite FTS5 + on-device vector KNN) over your AI coding-agent conversation history across 11 tools (Claude Code, Codex, Cursor, and more). Exposes search_threads, search_current_project, recent_threads, get_thread, list_tags, and list_open_todos so any agent can recall its own past work.