"Searching for 'Lightrag' MCP Server" matching MCP servers:

Enables AI agents to connect to a LightRAG knowledge-graph server over HTTP, exposing 33 tools for querying, managing documents, and editing knowledge graph entities and relations with proper authentication and error handling.

Enables AI assistants to interact with LightRAG knowledge graphs, supporting smart upsert for Obsidian vaults, semantic queries, and document/graph management.

MCP server for integrating LightRAG with AI tools. Provides a unified interface for interacting with LightRAG API through the MCP protocol.

Enables AI agents to query a persistent LightRAG knowledge base through any MCP client, offering both ready-made answers with source links and raw context retrieval for custom response generation.

Enables AI clients to interact with a LightRAG knowledge graph server via MCP, providing 30 tools for queries, document management, and graph operations.

Exposes a FastMCP server that proxies to an existing LightRAG Server API, enabling querying, document insertion, and management of a LightRAG knowledge base through MCP tools.

Bridges AI assistants with LightRAG's knowledge graph capabilities, enabling document management and multi-mode queries through the Model Context Protocol.

A comprehensive MCP server that provides full integration with LightRAG API, offering 22 tools across document management, querying, knowledge graph operations, and system management.

Enables AI coding agents to quickly search a LightRAG knowledge base without relying on an LLM, returning original notes with sources and graph relations, and to save decisions with timestamps.

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.

Provides a durable memory layer for coding agents like Claude Code and Codex by indexing codebases and enabling RAG queries, reducing rediscovery tokens and providing senior-engineer orientation.

Enables AI assistants to manage documents, query knowledge graphs, and perform retrieval-augmented generation using LightRAG with 30 tools and multiple query modes.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

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

Enables Codex projects to read Git-backed kickoff, acceptance, handoff, progress, and next-step context, and to append validated, audited progress events through scoped MCP tools. This supports visible agent progress, resumable sessions, and safer handoffs.

Enables AI agents to retrieve Git-backed project context, handoff packages, progress, and next steps, and to append validated progress events with matching project-record commits. This supports visible agent progress, resumable work, and safe handoffs while keeping high-risk actions outside the MCP surface.

Enables agents to read Git-backed project context and append audited, idempotent progress events through scoped, short-lived credentials, supporting resumable handoffs and visible project state.

Enables AI agents to read Git-backed project context and append validated, audited, idempotent progress events through short-lived, scoped credentials, supporting resumable work and safer handoffs.

A robust MCP server that transforms OneNote notebooks into an AI-accessible knowledge base for Gemini Spark, enabling natural language queries to list, read, and search notes via Microsoft Graph API.

Enables Codex agents to read a project's kickoff card, acceptance criteria, progress, Git trail, and handoff package, then append one validated, idempotent progress event with an agent verification note and matching Git commit. Access is limited to short-lived, scoped, revocable credentials bound to a single workspace and project, with high-risk actions kept outside the tool surface.

Enables MCP clients to read a project’s kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events as Git-backed project records.

Enables Codex and MCP clients to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events tied to project-record Git commits.

Enables agents to retrieve project context and append validated, audited progress events through scoped MCP tools, keeping project records Git-backed and handoffs resumable.

Enables AI agents to retrieve Git-backed project context—kickoff cards, acceptance criteria, handoffs, progress, and next actions—and to append validated, audited progress events under scoped credentials.

Enables Codex agents to pull a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, then append a single validated, audited, idempotent progress event with a matching project-record commit. Access is scoped to one short-lived, revocable credential bound to a single workspace and project.

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.

MCP server for Obsidian vaults, optimised for Cursor agents — safe note editing, lean tool surface, direct filesystem access.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

This MCP server provides a cost-optimized personal-knowledge brain, enabling AI agents to query imported documents via hybrid search and synthesis at minimal monthly spend.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.