Ollama Hive MCP Server

Name: Ollama Hive MCP Server
Author: Algiras

@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.