"Adding functionality to large language models" matching MCP servers:

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

MCP server that connects AI agents to Google NotebookLM, enabling natural language interaction with notebooks, including Q&A, source ingestion, and audio overview generation.

Enables local-first knowledge management for Codex, providing tools for guided discussions, contextual recall, review, and daily topics.

Builds a searchable memory bank from persona-specific PDF content and exposes it as an MCP tool for querying.

An MCP server that gives AI assistants complete, safe access to your Zotero library for searching, citing, adding papers, and formatting bibliographies, with local-first privacy.

Provides an external context buffer so a local model can maintain session memory across long tasks and search and page through large documents without loading them whole into its limited context window.

Enables per-project, traceable access to a RAG knowledge base, with tools for searching and adding knowledge chunks.

A standalone Node MCP server that provides semantic search, knowledge graph, and vault editing over an Obsidian vault. It runs locally as a single stdio process without requiring an Obsidian plugin for core functionality.

Provides spaced-repetition scheduling with the SM-2 algorithm as MCP tools, enabling agents to manage review items like flashcards or vocab locally. It supports adding, grading, and listing due items, plus optional pro features for export and forecast.

A server that summarizes and records conversation key points, supporting adding summaries and viewing history.

A server that wraps a self-hosted mem0 REST API as MCP tools for Claude Desktop and Claude Code, enabling memory operations such as adding, searching, and managing memories via natural language.

Enables an LLM to keep a persistent scratchpad by adding and reading notes, retrieving the latest note as context, and generating summaries through MCP.

An MCP server that enables Claude to interact with Google NotebookLM via browser automation, allowing management of notebooks, adding sources, and querying information.

Enables agents to manage persistent long-term memory through MCP tools for searching, adding, updating, giving feedback, and forgetting memories, with automated pipelines for redaction, distillation, and reconciliation.

Extends large language model context length up to 60 times using gravitational memory, designed for Claude Code and Anthropic AI models.

Enables agents to perform spaced-repetition learning with FSRS scheduling, including adding cards, reviewing due cards, and grading recall, using a headless SQLite or Postgres backend.

Enables fast code analysis and navigation through hybrid semantic search, graph-based relationship tracking, and structure exploration across multiple programming languages with optimized indexing for large codebases.

Enables AI agents to persistently recall, apply, and reinforce solutions to previously solved problems across different models and tools, so mistakes are not repeated.

Enables personal AI memory management through MCP tools for adding, searching, exporting, and deleting memories, with knowledge-graph retrieval and multi-hop association for clients like Claude Desktop and Cursor.