A
licenseB
qualityD
maintenanceMCP Ollama server integrates Ollama models with MCP clients, allowing users to list models, get detailed information, and interact with them through questions.
3
33
MIT
MCP Ollama Consult Server
by Atomic-Germ
This MCP server enables AI agents to consult with multiple Ollama models for diverse perspectives, collaborative reasoning, and persistent memory management.
Core Capabilities:
Consult Individual Models - Send prompts to specific Ollama models with optional system prompts for guided reasoning
List Available Models - Discover all models available on your local or remote Ollama instance
Compare Multiple Models - Run identical prompts against multiple models simultaneously for side-by-side output comparisons
Sequential Reasoning Chains - Execute complex multi-step workflows where subsequent consultations build upon previous results
Persistent Memory Storage - Save consultation results (key, prompt, model, response) to configured memory services or local file storage for cross-session retrieval
Timeout Management - Configure specific time limits (60-600 seconds) for complex reasoning tasks without losing context
Flexible Integration - Works with any MCP-compatible client (like Claude Desktop) through the Model Context Protocol
Enables consulting with Ollama models for alternative reasoning viewpoints, with tools for sending prompts to models and listing available models on the Ollama instance.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Ollama Consult Servercompare llama3 and mistral on how to improve team collaboration"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Ollama Consult Server
An MCP (Model Context Protocol) server that allows consulting with Ollama models for reasoning from alternative viewpoints.
Features
consult_ollama: Send prompts to Ollama models and get responses
list_ollama_models: List available models on the local Ollama instance
compare_ollama_models: Run the ame prompt against multiple Ollama models and return their outputs side-by-side for comparison
remember_consult: Store the result of a consult into a local memory store (or configured memory service)
Related MCP server: Ollama MCP Server
Installation
Install the server:
npm i -g https://github.com/Atomic-Germ/mcp-consult/releases/download/v1.0.1/mcp-ollama-consult-1.0.1.tgzConfigure the server:
{ "servers": { "ollama-consult": { "type": "stdio", "command": "mcp-ollama-consult", "args": [] } }, "inputs": [] }
Usage
Make sure Ollama is running locally (default: (http://localhost:11434).
Start the MCP server:
mcp-ollama-consultOr for development:
npm run devConfiguration
Set the OLLAMA_BASE_URL environment variable to change the Ollama endpoint:
OLLAMA_BASE_URL=http://your-ollama-server:11434 npm startDocker
To run with Docker, build the image:
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY dist/ ./dist/
CMD ["node", "dist/index.js"]Requirements
Node.js 18+
Ollama running locally or accessible via HTTP
Maintenance
–Maintainers
–Response time
–Release cycle
1Releases (12mo)
Commit activity
Resources
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If you are the server author, to access and configure the admin panel.
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