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

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    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.
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    133,826
    Inno Setup
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    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.
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    MIT
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    Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.
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    MIT
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    MCP server that turns Kimi K2.6 Turbo into an agentic coding assistant with tools for file operations, shell commands, and code search.
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    MIT
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    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.
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    5,825
    AGPL 3.0
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    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.
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    ISC
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    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.
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    Apache 2.0
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    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.
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    Enables Claude or any MCP client to drive the GitHub Copilot cloud agent via its REST API, allowing it to research, edit, and open pull requests on repositories without manual intervention.
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    MIT
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    A Model Context Protocol (MCP) server providing 62 AI-optimized tools for .NET/C# semantic code analysis, navigation, refactoring, and code generation using Microsoft Roslyn. Built for AI coding agents - provides compiler-accurate code understanding that AI cannot infer from reading source files alone.
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    MIT
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    Agentic MCP server that receives a feature specification from an IDE, autonomously implements it in an isolated sandbox via an internal loop (plan-act-validate-correct), and returns a structured report with diffs and test results, without modifying the original repository.
    4
    MIT
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    Provides IDE-like semantic code retrieval and editing tools for LLMs, enabling precise code understanding and manipulation in large codebases via the Model Context Protocol.
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    MIT
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    A fully local, privacy-first MCP server that gives AI coding assistants deep repository intelligence with file-and-line-cited answers, persistent semantic memory, and agentic abilities like task planning and code review—all without any cloud API calls.
    23