"Agentic RAG: Understanding or Exploring Its Meaning and Applications" matching MCP servers:

Long-term memory for Claude Desktop and Claude Code over plain markdown files on your machine. It returns nothing when the corpus has no answer, naming the terms that appear nowhere — no least-bad match dressed as an answer. And it verifies cited commit SHAs against git, so an agent can tell what actually shipped from what was only discussed and abandoned. Local; nothing is transmitted.

Enables ChatGPT Web Developer Mode to interact with local repositories through MCP, providing tools for file editing, shell execution, Git worktrees, semantic navigation, and checkpoints.

Enables a fully local multi-agent AI system with 45 specialized agents and 50 predefined workflows via MCP, powered by Ollama and requiring no internet.

MCP server that enables an agent to autonomously build, compile-check, test, and debug DayZ mods, integrating with the running game via a server bridge and providing structured verdicts, world manipulation, client control, and API knowledge indexing.

Enforces a git-tracked, code-checked finite state machine that hands control between a planning director and a local Ollama implementor, exposing tools to check phase status, transition states, and run the implementor to execute plan step files one at a time. It enables a project to be planned, implemented step by step with per-step test gating, and validated before completion.

Enables structured, step-by-step problem-solving through dynamic thinking processes that can be revised, branched, and adjusted as understanding deepens. Supports breaking down complex problems into manageable steps with the ability to revise previous thoughts and explore alternative reasoning paths.

Exposes the four Ejentum cognitive harnesses (reasoning, code, anti-deception, memory) as MCP tools any agentic client can call. Drop-in scaffolding that catches LLM failure modes like sycophancy, hallucination, and reasoning shortcuts.

Delegates coding tasks to the locally installed Kimi Code CLI, reusing its auth, models, and configuration while adding tools for sessions, replies, model discovery, live turn steering, and history access.

Spawn parallel autonomous AI agent sessions from a single MCP client. Each agent gets its own workspace, tools, and execution context.

Enables AI coding agents like Claude Code or Codex to delegate tasks to a DeepSeek Harness subagent with its own context window, providing tools for task delegation, result waiting, continuation, and supervision with sandboxed execution.

MCP server that turns Kimi K2.6 Turbo into an agentic coding assistant with tools for file operations, shell commands, and code search.

Wraps the Claude Agent SDK as MCP servers, letting you spawn multiple specialized Claude Code agents — each with its own model, tools, system prompt, and personality — from any MCP client.

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

Prevents coding agents from repeatedly attempting the same failed fix by tracking attempts and blocking further fixes until the agent uses its own web search tool.

MCP server that runs JetBrains' ReSharper command-line tools for code inspection and cleanup, exposed to C# coding agents over stdio.

Enables AI agents to perform software engineering tasks inside an isolated, deterministic sandbox—exploring repositories, reproducing failures, applying patches, running tests, and verifying solutions against hidden suites through MCP tools.

Enables AI coding agents to compile, test, run, hot-swap, and debug Java applications incrementally through MCP, providing runtime feedback for verifying code changes.

An MCP server that splits coding work between ChatGPT web (planning, review) and Codex CLI (implementation), enabling agentic workflows over a local repo with risk-gated execution and safety rails.

MCP server that analyzes videos locally with frame-by-frame understanding and optional browser sidecars, producing structured context bundles for coding agents to fix bugs, add features, or build new functionality.