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AegnticMCP MCP Server

@aegntic

代码仓库

基本信息

分类

其他

许可证

NOASSERTION

传输方式

stdio

作者

aegntic

关于 AegnticMCP MCP Server

AegnticMCP automates the creation and management of MCP servers, ensuring they are stable, adaptable, and intelligent.

#mathgpt#math-solver#math-assistant

AegnticMCP MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "aegnticMCP": {
      "command": "docker",
      "args": [
        "run",
        "-d",
        "--name",
        "qdrant",
        "-p",
        "6333:6333",
        "-v",
        "$(pwd)/data/qdrant:/qdrant/storage",
        "qdrant/qdrant:latest"
      ]
    }
  }
}

AegnticMCP MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is AegnticMCP?

AegnticMCP is a Retrieval-Augmented Generation (RAG) system that transforms Obsidian vaults into AI-paired cognitive workflow engines with advanced Graphiti knowledge graph integration. It is built for developers and knowledge workers who want to query their Obsidian notes using Claude Code.

How to use AegnticMCP?

Install via pip (pip install obsidian-elite-rag-mcp) or from source. Run obsidian-elite-rag-cli setup and obsidian-elite-rag-cli start-databases to initialize databases, then ingest your vault with obsidian-elite-rag-cli ingest /path/to/vault. Start the MCP server with obsidian-elite-rag-cli server and configure Claude Code by adding the server entry to ~/.config/claude-code/config.json.

Key features of AegnticMCP

  • Multi-layer RAG architecture with six retrieval layers
  • Advanced Graphiti knowledge graph with 27+ entity and 40+ relationship types
  • Dual-graph architecture: Neo4j (structured) + NetworkX (unstructured backup)
  • Full MCP server implementation compatible with Claude Code
  • CLI tools for setup, ingestion, querying, and graph search
  • Real-time system status monitoring and database connection checks

Use cases of AegnticMCP

  • Ingest an entire Obsidian vault and query it using Claude Code
  • Search for entities and relationships in your knowledge graph
  • Retrieve context-rich answers combining semantic, graph, and temporal signals
  • Automate knowledge tasks like linking notes or extracting entities

常见问题

1

What are the dependencies for AegnticMCP?

Python 3.9+, Docker & Docker Compose, an OpenAI API key, and optionally an Obsidian vault. Neo4j and Qdrant databases are handled by the setup scripts.

2

How do I install AegnticMCP?

Install from PyPI with `pip install obsidian-elite-rag-mcp` or clone the repository and run `pip install -e .` in the `obsidian-elite-rag` directory.

3

How do I connect AegnticMCP with Claude Code?

Start the MCP server using `obsidian-elite-rag-cli server`, then add a server entry to `~/.config/claude-code/config.json` with the command and environment variable `OPENAI_API_KEY`.

4

What query types does AegnticMCP support?

The CLI supports general, technical, and research queries. The MCP tools provide `query_rag`, `search_knowledge_graph`, `get_entity_context`, `get_related_entities`, and more.

5

What are the performance characteristics of AegnticMCP?

Retrieval speed under 100ms for context-rich queries, knowledge coverage over 95% recall on domain-specific queries, entity recognition accuracy above 90%, and graph traversal under 50ms up to depth 4.

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