Browse all Model Context Protocol servers with quality scores, stars, languages and maintenance activity.
A Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, and search atomic notes through Claude and other MCP-compatible clients.
Hierarchical memory engine for AI agents with automatic decay, promotion, semantic dedup, and self-organizing topic tree. Single Rust binary, zero external dependencies.
Persistent memory for AI coding assistants with hybrid search (FTS5 + vector embeddings), session tracking, automatic context hooks, and web viewer. SQLite-based with no daemon process — works with Claude Code, Cursor, Windsurf, and any MCP client.
An MCP server that stores and retrieves memories from multiple LLMs using MongoDB. Provides tools for saving, retrieving, adding, and clearing conversation memories with timestamps and LLM identification.
AI-powered paper annotation MCP server. Reads papers, highlights key findings with semantic color coding, explains formulas, and writes structured reading notes — all saved back to Zotero. Features two-phase workflow for large PDFs (63–80% context savings) and batch annotations.
Persistent 4-tier AI memory (episodic, semantic, project, procedural) with temporal scoring, contradiction detection, entity tracking, and real-time desktop visualization orb.
Production-grade persistent memory service for AI agents. Semantic search with recency decay (configurable α blend), local ONNX embeddings (zero API cost), background memory summarisation, and Prometheus/Grafana observability. `docker compose up` — no cloud dependencies.
Read Markdown with inlined images and heading indexes for agentic RAG over local docs or allowed URLs.
Persistent fractal graph memory for AI coding agents via MCP. Semantic vector search, hot/cold/archive context tiers, decision tracking, and Docker-based deployment with Qdrant.
Query and summarize your chat messages with AI prompts.
Intelligent agent memory with semantic recall, automatic consolidation, contradiction detection, and bi-temporal knowledge graph. 80% on LOCOMO benchmark using 96% fewer tokens than full-context approaches.
An MCP server that enables cross-LLM communication and memory sharing, allowing different AI models to collaborate and share context across conversations.
Hosted MCP server by [PapersFlow](https://papersflow.ai) for academic research with 7 specialized AI agents and 474M+ papers from Semantic Scholar and OpenAlex. Literature search, citation verification, citation graph exploration, and autonomous deep research workflows.
Self-hosted memory and governance layer for AI coding agents. 28 MCP tools with structured knowledge capture, hybrid search (semantic + BM25 + cross-encoder reranking), behavioral documentation nudges, cold-start codebase analyzer, and git-native storage. Single Docker container, zero cloud dependencies.
Local-first project memory and guardrails for coding agents. Records failed attempts, fragile files, and decisions per repo; warns the agent before it repeats a recorded mistake. `npx -y memini mcp`
Shared, versioned memory for your agents across Claude Code, Cursor, Kiro and Grok. One MCP server, sourced answers, full history. Remote Streamable HTTP; anonymous browses a public demo corpus. Tools: `search`, `get_context_pack`, `upsert_document`. `https://basemouse.com/mcp`
Compiles saved YouTube videos, podcasts, articles, PDFs, and Notion/Obsidian notes into a persistent, semantically searchable knowledge base any AI can query over MCP.
Agent-first cross-platform bookmark & knowledge manager. AI agents collect web pages from any source (pairs naturally with Fetch, Firecrawl, Brave Search) and auto-categorize into organized collections with search, tags, and shared folders. 16 tools including `agent_register` (zero-config onboarding), `add_footprint`, `search_footprints`, `create_shared_category`. `pip install -r requirements.txt
Persistent memory for AI agents through a simple key-value HTTP API. No vector database or embeddings required. Store, retrieve, search, and share memory across agents with shared namespaces and TTL support. `npx -y agentram-mcp`
Five-level AI collaboration system with persistent memory and anticipatory capabilities. MCP-native integration for Claude and other LLMs with local-first architecture via MemDocs.
Shared knowledge base where AI agents exchange proven solutions — including failed approaches, so your agent skips the dead ends. Smaller models get instant access to frontier-model discoveries. Free to search indefinitely when feedback is provided on results. [Website](https://prior.cg3.io)
A Model Context Protocol server for Mem0 that helps manage coding preferences and patterns, providing tools for storing, retrieving and semantically handling code implementations, best practices and technical documentation in IDEs like Cursor and Windsurf
Read and write Apple Notes with bidirectional Markdown conversion. Fast SQLite queries for listing/searching, AppleScript + native import for full CRUD. Supports stdio and Streamable HTTP transports.
Persistent identity architecture for AI agents. 16 MCP servers covering drives, emotional relationships, semantic memory with decay, working threads, learned patterns, journal, genesis (identity discovery), creative collision engine, forecasting, and voice. Zero dependencies beyond Python 3.8. Built across 938 conversations.
AI coding context for Claude Code, Cursor, and Codex. Path-scoped team memories, rules, and skills from Pathrule Web workspaces via OAuth. `https://mcp.pathrule.io/mcp`
A connector for LLMs to work with collections and sources on your Zotero Cloud
Versioned, structured memory for AI agents. Stores facts as keypaths with full version history, automatic conflict detection, and O(1) token retrieval.
Persistent codebase knowledge layer for AI coding agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) via tree-sitter native parsing (28 languages) and serves via MCP. 14 tools, ~85% token reduction. Works with Claude Code, Cursor, Codex, and any MCP client.
Lightweight local RAG MCP server for semantic vector search over markdown documents. Reduces token consumption by 40x with sqlite-vec and multilingual-e5-small embeddings. Supports filtered search by directory and filename patterns.
AI agent knowledge marketplace where agents share solutions and earn tokens. Search, publish, and unlock previously solved problems to reduce token usage and computational costs.
Penfield: persistent memory with hybrid search (BM25 + vector + graph), 24 relationship types for knowledge graphs, context checkpoints for cognitive handoff, artifact storage, and personality system. Works across Claude, Cursor, Windsurf, and any MCP client.
Persistent, searchable context storage across Claude Code sessions using SQLite FTS5. Save sessions with AI-generated summaries, two-tier full-text search, checkpoint recovery, and a web dashboard.
Search 1,500+ pre-verified, cited knowledge units across 16 domains. 6 tools: query, batch query, get unit, list domains, suggest topics, report issues. Confidence scores, source provenance, and freshness tracking. Free, no API key required.
Knowledge graph-based persistent memory system for maintaining context
Local workspace memory for Claude Desktop. Indexes your documents (Markdown, CSV, session logs) into a vector store with hybrid search, cross-session memory, auto-learn, and knowledge graph visualization. Zero external dependencies — fastembed + LanceDB, no Ollama or Docker required. 15 MCP tools.
Persistent memory MCP server with OS-style demand paging, kswapd-style eviction, and mlock pinning. Multi-agent shared SQLite store with BM25 + FTS5 retrieval, importance scoring, and capacity-aware reclaim. 5 tools: `memory_lookup`, `pin_memory`, `unpin_memory`, `memory_stats`, `list_pinned`. `uvx --from git+https://github.com/soolaugust/0CompactMem memory-os`
Make any website queryable by AI agents. Index a site then ask questions and get cited answers grounded in its content via RAG. Tools: `list_sites` and `ask_site`. `npx -y @agentreadyweb/mcp`
Enable AI assistants to conduct structured, persona-driven sessions including interview preparation, personal reflection, and coaching conversations. Built-in timer management and performance evaluation tools.
Deterministic reasoning engine for AI agent context compression. Extracts structured facts with logical inference, proof chains, and truth maintenance. REST API, Python/TypeScript SDKs, and MCP server integration.
Governed memory for coding agents with trust lifecycle (hypothesis → active → validated → deprecated), conflict detection, staleness tracking, and health scoring. SQLite + FTS5, zero infrastructure. `pip install quilmem[mcp]`
Shared research cache across AI agents. Hit → instant answer from verified sources. Miss → your research saves the next dev's tokens. `npx wellread`, free.
Validate and generate SOUL.md agent identity files from Claude Desktop. SOUL.md is the open format for persistent AI agent identity — personality, voice, values, and behavioral constraints in a machine-readable YAML file.
RAG for PDFs, YouTube, GitHub repos, Discord exports; index documents and query with citations.
Smart memory with exponential decay. Memories strengthen on access and fade when unused — solving the Karpathy problem of unbounded context growth. 7 tools, SQLite-based, zero dependencies.
Local-first long-term memory for terminal AI agents (Claude Code et al.) via Anchored Compacting. Stores blueprints, code anchors (file→line→concept), and distilled lessons in a single JSON under `.zipmem/`, restoring full cross-session project context at near-zero token cost. No DB, no API keys, no embeddings. `npx zipmem-mcp`
One shared context for every AI tool your team uses. Serves your team's knowledge, coding standards, skills, and AI agents to Claude, Cursor, Copilot, and any MCP client — load a whole workflow (docs, agents, skills, tasks, phases) in a single call. Versioned and permissioned. `npx @contextium/mcp-server`
AI Summarization MCP Server, Support for multiple content types: Plain text, Web pages, PDF documents, EPUB books, HTML content
Chat with 36 legendary founders & investors (Elon Musk, Warren Buffett, Steve Jobs, CZ). AI personas with authentic voices, frameworks, and principles. No API key required.