"Resources to Become an Expert in LangChain" matching MCP servers:

Enables MCP-compatible agents to query beliefs, search documents, and explore reasoning chains from expert-service knowledge bases.

MCP server for a personal knowledge graph running on Cloudflare, enabling note-taking, task management, and cross-domain recall via Claude.

Builds a queryable knowledge graph from a pack of repos, papers, and notes, and serves it to agents via MCP, enabling search, source reading, and neighbor exploration.

Persistent memory and pattern learning for AI coding assistants via MCP.

An MCP server integrating LangChain, RAG, and Agent to provide knowledge retrieval and tool invocation through natural language.

A high-performance MCP server for expert discovery, registration, and context injection, enabling AI-powered expert selection through semantic search and relationship modeling with vector and graph database integration.

Enables hybrid retrieval over interpretable Gemini documentation knowledge graphs through eight MCP tools, combining vector, keyword, and graph-boosted search with deprecation filtering.

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.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

Enables agents to run hybrid retrieval, reciprocal rank fusion, knowledge graph expansion, semantic caching, and context reordering so critical evidence is placed at prompt boundaries to reduce lost-in-the-middle degradation.

A Python-based system that provides AI-powered code reviews through simulated expert personas like Martin Fowler and Robert C. Martin, using the Model Context Protocol (MCP).

Enables AI assistants to query and retrieve a structured professional profile, including expertise areas, CV, projects, active research, and target AI queries, through dedicated MCP tools and resources.

Enables AI coding agents to retain and recall project context across sessions through local Markdown storage and hybrid keyword/semantic retrieval, including reusable knowledge cards. It runs offline as a daemon and integrates with MCP-compatible IDEs to continue long-running work without re-explaining decisions or architecture.

Enables insurance claims review assistance by querying a knowledge graph of Korean standard insurance terms, restoring applicable policy versions by enrollment date, and returning coverage/exclusion determinations with cited provisions.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

Enables a simulated Alexa+ care companion to capture daily check-ins, recall longitudinal care-journal history, assess risk, create local family-inbox cards, schedule follow-ups, and produce weekly digests through MCP tools.

Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.

Local-first MCP server that extracts structured knowledge from markdown notes into SQLite with full-text search, enabling AI coding tools to retrieve relevant context offline at zero cost.

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.

Your team's prompt, rules, skills & docs library exposed over MCP (search_library + get_item); mark items "/" and they become slash commands. Free for individuals.

Metis gives AI agents expert know-how that named reviewers have approved, and only where its recorded conditions match the situation. High-risk situations go to a person. When an agent sees practice depart from procedure, it can send the expert one short question. Every retrieval is recorded on a hash-linked evidence chain.

Turns team chat (Slack, Discord, MS Teams, Mattermost) into a living knowledge base - a typed knowledge graph plus auto-generated wiki - exposed to AI agents through a 28-tool MCP server with semantic search, expert finding, and decision tracing.

Provides tools for managing student knowledge graphs, enabling structured representation of courses, assignments, exams, concepts, and study resources.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

A self-hostable, open-source, semantically-searchable Agent Skills registry delivered over MCP, with a three-tier progressive disclosure architecture.

MCP server for Woody, an AI firearms expert that answers questions with verified citations, checks state-specific laws, and routes to specialist agents.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.