"A server for semantic API information and resources" matching MCP servers:

Enables MCP clients to serve and query semantic models, providing tools for entity descriptions, metric lookups, context resolution, and operation validation for AI agents.

Persistent memory with semantic search for Claude and MCP-compatible clients, storing context that survives conversations and can be retrieved intelligently.

Reduces token consumption by over 80% through intelligent file caching, returning only diffs for modified files and suppressing unchanged content. It features a suite of 12 tools for semantic search, batch reading, and efficient file editing to optimize LLM interactions with large codebases.

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

A persistent memory layer for Claude Desktop that enables semantic search across your entire Obsidian vault using local embeddings and PostgreSQL + pgvector.

Enables AI assistants to save, load, and search conversation context with AI-powered summarization and auto-tagging. Demonstrates semantic intent patterns and hexagonal architecture for maintainable AI-assisted development.

Provides tools for named entity extraction, Wikidata disambiguation, sameAs schema linking, and knowledge graph triple construction, enabling structured semantic data processing.

A persistent memory layer for Claude Desktop that enables semantic search and CRUD operations on your Obsidian vault using local embeddings and PostgreSQL+pgvector.

Enables fully local semantic search over a Roam Research graph via MCP, providing tools for hybrid retrieval, index refresh, and stats while keeping all content on-machine.

Enables AI agents to store, search, and recall semantic memories with three memory types (semantic, episodic, procedural) and auto-consolidation, compounding intelligence over time.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

An MCP server that provides governed metric definitions and provenance-labeled memory for materials test labs, enforcing quality system discipline on agent interactions.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables Claude to store and retrieve information with semantic search using Qdrant vector database, providing persistent memory for conversations, code, and documentation.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

A local semantic search MCP server for Markdown vaults that indexes and retrieves notes using hybrid keyword and embedding search.

Persists Claude Code sessions to Notion as team memory, enabling queryable recall of decisions, work state, and project architecture.

Enables semantic search over local notes and documents using natural language queries. Supports multiple file types (Markdown, Python, HTML, JSON, CSV, text) with fast local embeddings and persistent ChromaDB vector storage.

A bridge between MCP Host applications and mem0 cloud service, specialized for project management with capabilities to store, retrieve, and search project information within a structured format.

Unofficial Notion MCP server built on Notion's private API (token_v2 cookie). Gives LLM agents full read/write access to the entire workspace — no integration token and no per-page sharing.