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Ollama Hive MCP Server

@Algiras

代码仓库

关于 Ollama Hive MCP Server

暂无概览

#ollama#mcp-server#langchain

基本信息

分类

AI 与智能体

运行时

node

传输方式

stdio

发布者

Algiras

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "ollama-hive-mcp-server": {
      "command": "npx",
      "args": [
        "ollama-hive-mcp-server"
      ]
    }
  }
}

工具

未检测到工具

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 Ollama Hive MCP Server?

A TypeScript-based Model Context Protocol (MCP) server that integrates with Ollama models using LangChain. It provides tools and resources for querying local language models through a standardized MCP interface, with model-specific MCP server configurations.

How to use Ollama Hive MCP Server?

Run directly via npx: npx ollama-hive-mcp-server. Optionally set MCP_CONFIG_PATH and environment overrides. For persistent installation, clone the repository, install dependencies, build, and start with npm start. The server exposes tools like query_model, test_model, get_model_info, and list_models.

Key features of Ollama Hive MCP Server

  • Model management: configure multiple Ollama models with per-model endpoints and settings.
  • Model-specific MCP servers: each model can have its own set of MCP tools.
  • Session management: conversation sessions for context continuity across queries.
  • Environment variable support: override endpoints and configuration via environment variables.
  • Stdio transport: standard input/output communication for seamless integration.
  • Pre-loading: all models loaded at startup for quick responses.

Use cases of Ollama Hive MCP Server

  • Query local Ollama language models from any MCP client (e.g., Claude Desktop, Cursor IDE).
  • Build multi-turn conversations with session-based context retention.
  • Provide specialized tool sets per model (e.g., filesystem for code model, web search for research model).
  • Test and debug model connectivity and MCP server configurations.

FAQ from Ollama Hive MCP Server

What runtime does it require?

Node.js 18+ and an Ollama instance running locally (default http://localhost:11434).

How are model endpoints resolved?

Priority: 1) OLLAMA_ENDPOINT environment variable, 2) model-specific endpoint config, 3) global globalEndpoint config, 4) default http://localhost:11434.

How do I use sessions for context continuity?

Create a session with the create_session tool, then pass the returned sessionId to subsequent query_model calls. Alternatively, set createSession: true to auto-create a session.

Are MCP servers isolated per model?

Yes. Each model can define its own set of MCP servers; they are isolated from other models.

How is configuration validated?

All configuration is validated using Zod schemas; errors are returned in a standardized format.

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